Tue, 23 Apr 2024

Package vdg updated to version 1.2.3 with previous version 1.2.2 dated 2022-07-07

Title: Variance Dispersion Graphs and Fraction of Design Space Plots
Description: Facilities for constructing variance dispersion graphs, fraction- of-design-space plots and similar graphics for exploring the properties of experimental designs. The design region is explored via random sampling, which allows for more flexibility than traditional variance dispersion graphs. A formula interface is leveraged to provide access to complex model formulae. Graphics can be constructed simultaneously for multiple experimental designs and/or multiple model formulae. Instead of using pointwise optimization to find the minimum and maximum scaled prediction variance curves, which can be inaccurate and time consuming, this package uses quantile regression as an alternative.
Author: Pieter Schoonees [aut, cre, cph], Niel le Roux [ctb]
Maintainer: Pieter Schoonees <schoonees@gmail.com>

Diff between vdg versions 1.2.2 dated 2022-07-07 and 1.2.3 dated 2024-04-23

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Package FjordLight updated to version 0.8 with previous version 0.7.0 dated 2023-12-02

Title: Available Light Within the Water Column and Seafloor of Arctic Fjords
Description: Satellite data collected between 2003 and 2022, in conjunction with gridded bathymetric data (50-150 m resolution), are used to estimate the irradiance reaching the bottom of a series of representative EU Arctic fjords. An Earth System Science Data (ESSD) manuscript, Schlegel et al. (2023, in review), that provides a detailed explanation of the methodology is currently in review.
Author: Bernard Gentili [aut], Jean-Pierre Gattuso [aut] , Robert W. Schlegel [aut, cre]
Maintainer: Robert W. Schlegel <robert.schlegel@imev-mer.fr>

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Package SIAmodules updated to version 0.1.1 with previous version 0.1.0 dated 2023-03-29

Title: Modules for 'ShinyItemAnalysis'
Description: Package including additional modules for interactive 'ShinyItemAnalysis' application for the psychometric analysis of educational tests, psychological assessments, health-related and other types of multi-item measurements, or ratings from multiple raters.
Author: Patricia Martinkova [aut, cre] , Jan Netik [aut]
Maintainer: Patricia Martinkova <martinkova@cs.cas.cz>

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Package scGate updated to version 1.6.2 with previous version 1.6.0 dated 2023-11-06

Title: Marker-Based Cell Type Purification for Single-Cell Sequencing Data
Description: A common bioinformatics task in single-cell data analysis is to purify a cell type or cell population of interest from heterogeneous datasets. 'scGate' automatizes marker-based purification of specific cell populations, without requiring training data or reference gene expression profiles. Briefly, 'scGate' takes as input: i) a gene expression matrix stored in a 'Seurat' object and ii) a “gating model” (GM), consisting of a set of marker genes that define the cell population of interest. The GM can be as simple as a single marker gene, or a combination of positive and negative markers. More complex GMs can be constructed in a hierarchical fashion, akin to gating strategies employed in flow cytometry. 'scGate' evaluates the strength of signature marker expression in each cell using the rank-based method 'UCell', and then performs k-nearest neighbor (kNN) smoothing by calculating the mean 'UCell' score across neighboring cells. kNN-smoothing aims at compensating for the large degree of s [...truncated...]
Author: Massimo Andreatta [aut, cre] , Ariel Berenstein [aut] , Josep Garnica [aut], Santiago Carmona [aut]
Maintainer: Massimo Andreatta <massimo.andreatta@unil.ch>

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Package qspray updated to version 3.0.0 with previous version 2.1.1 dated 2023-09-07

Title: Multivariate Polynomials with Rational Coefficients
Description: Symbolic calculation and evaluation of multivariate polynomials with rational coefficients. This package is strongly inspired by the 'spray' package. It provides a function to compute Gröbner bases (reference <doi:10.1007/978-3-319-16721-3>). The header file of the C++ code can be used by other packages. It provides the templated class 'Qspray' that can be used to represent and to deal with multivariate polynomials with another type of coefficients.
Author: Stephane Laurent [aut, cre], Robin Hankin [ctb, cph]
Maintainer: Stephane Laurent <laurent_step@outlook.fr>

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Package NMdata updated to version 0.1.6 with previous version 0.1.5 dated 2024-02-21

Title: Preparation, Checking and Post-Processing Data for PK/PD Modeling
Description: Efficient tools for preparation, checking and post-processing of data in PK/PD (pharmacokinetics/pharmacodynamics) modeling, with focus on use of Nonmem. Attention is paid to ensure consistency, traceability, and Nonmem compatibility of Data. Rigorously checks final Nonmem datasets. Implemented in 'data.table', but easily integrated with 'base' and 'tidyverse'.
Author: Philip Delff [aut, cre], Eric Anderson [ctb]
Maintainer: Philip Delff <philip@delff.dk>

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Package evd updated to version 2.3-7 with previous version 2.3-6.1 dated 2022-07-04

Title: Functions for Extreme Value Distributions
Description: Extends simulation, distribution, quantile and density functions to univariate and multivariate parametric extreme value distributions, and provides fitting functions which calculate maximum likelihood estimates for univariate and bivariate maxima models, and for univariate and bivariate threshold models.
Author: Alec Stephenson. Function fbvpot by Chris Ferro.
Maintainer: Alec Stephenson <alec_stephenson@hotmail.com>

Diff between evd versions 2.3-6.1 dated 2022-07-04 and 2.3-7 dated 2024-04-23

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Package syt updated to version 0.4.0 with previous version 0.3.0 dated 2023-12-06

Title: Young Tableaux
Description: Deals with Young tableaux (field of combinatorics). For standard Young tabeaux, performs enumeration, counting, random generation, the Robinson-Schensted correspondence, and conversion to and from paths on the Young lattice. Also performs enumeration and counting of semistandard Young tableaux, enumeration of skew semistandard Young tableaux, and computation of Kostka numbers.
Author: Stephane Laurent
Maintainer: Stephane Laurent <laurent_step@outlook.fr>

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Package shinyDatetimePickers updated to version 1.2.0 with previous version 1.1.0 dated 2023-08-07

Title: Some Datetime Pickers for 'Shiny'
Description: Provides three types of datetime pickers for usage in a 'Shiny' UI. A datetime picker is an input field for selecting both a date and a time.
Author: Stephane Laurent [aut, cre], Wojciech Maj [cph] ), Porinn [cph] ), Dmitriy Kovalenko [cph] )
Maintainer: Stephane Laurent <laurent_step@outlook.fr>

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Package MAGEE updated to version 1.4.0 with previous version 1.3.2 dated 2023-11-17

Title: Mixed Model Association Test for GEne-Environment Interaction
Description: Use a 'glmmkin' class object (GMMAT package) from the null model to perform generalized linear mixed model-based single-variant and variant set main effect tests, gene-environment interaction tests, and joint tests for association, as proposed in Wang et al. (2020) <DOI:10.1002/gepi.22351>.
Author: Xinyu Wang [aut], Han Chen [aut, cre], Duy Pham [aut], Kenneth Westerman [ctb], Cong Pan [aut], Eric Biggers [ctb, cph] , Tino Reichardt [ctb, cph] library), Meta Platforms, Inc. and affiliates [cph] library)
Maintainer: Han Chen <han.chen.2@uth.tmc.edu>

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Package kantorovich updated to version 3.2.0 with previous version 3.1.0 dated 2023-08-22

Title: Kantorovich Distance Between Probability Measures
Description: Computes the Kantorovich distance between two probability measures on a finite set. The Kantorovich distance is also known as the Monge-Kantorovich distance or the first Wasserstein distance.
Author: Stephane Laurent
Maintainer: Stephane Laurent <laurent_step@outlook.fr>

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Package greeks updated to version 1.4.2 with previous version 1.3.5 dated 2024-03-03

Title: Sensitivities of Prices of Financial Options and Implied Volatilities
Description: Methods to calculate sensitivities of financial option prices for European, geometric and arithmetic Asian, and American options, with various payoff functions in the Black Scholes model, and in more general jump diffusion models. A shiny app to interactively plot the results is included. Furthermore, methods to compute implied volatilities are provided for a wide range of option types and custom payoff functions. Classical formulas are implemented for European options in the Black Scholes Model, as is presented in Hull, J. C. (2017), Options, Futures, and Other Derivatives. In the case of Asian options, Malliavin Monte Carlo Greeks are implemented, see Hudde, A. & Rüschendorf, L. (2023). European and Asian Greeks for exponential Lévy processes. <doi:10.1007/s11009-023-10014-5>. For American options, the Binomial Tree Method is implemented, as is presented in Hull, J. C. (2017).
Author: Anselm Hudde [aut, cre]
Maintainer: Anselm Hudde <anselmhudde@gmx.de>

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Package ggplot2 updated to version 3.5.1 with previous version 3.5.0 dated 2024-02-23

Title: Create Elegant Data Visualisations Using the Grammar of Graphics
Description: A system for 'declaratively' creating graphics, based on "The Grammar of Graphics". You provide the data, tell 'ggplot2' how to map variables to aesthetics, what graphical primitives to use, and it takes care of the details.
Author: Hadley Wickham [aut] , Winston Chang [aut] , Lionel Henry [aut], Thomas Lin Pedersen [aut, cre] , Kohske Takahashi [aut], Claus Wilke [aut] , Kara Woo [aut] , Hiroaki Yutani [aut] , Dewey Dunnington [aut] , Teun van den Brand [aut] , Posit, PBC [cph, [...truncated...]
Maintainer: Thomas Lin Pedersen <thomas.pedersen@posit.co>

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Package inTrees updated to version 1.4 with previous version 1.3 dated 2022-05-31

Title: Interpret Tree Ensembles
Description: For tree ensembles such as random forests, regularized random forests and gradient boosted trees, this package provides functions for: extracting, measuring and pruning rules; selecting a compact rule set; summarizing rules into a learner; calculating frequent variable interactions; formatting rules in latex code. Reference: Interpreting tree ensembles with inTrees (Houtao Deng, 2019, <doi:10.1007/s41060-018-0144-8>).
Author: Houtao Deng [aut, cre], Xin Guan [aut], Vadim Khotilovich [aut]
Maintainer: Houtao Deng <softwaredeng@gmail.com>

Diff between inTrees versions 1.3 dated 2022-05-31 and 1.4 dated 2024-04-23

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Package CCAMLRGIS updated to version 4.0.8 with previous version 4.0.7 dated 2024-02-05

Title: Antarctic Spatial Data Manipulation
Description: Loads and creates spatial data, including layers and tools that are relevant to the activities of the Commission for the Conservation of Antarctic Marine Living Resources. Provides two categories of functions: load functions and create functions. Load functions are used to import existing spatial layers from the online CCAMLR GIS such as the ASD boundaries. Create functions are used to create layers from user data such as polygons and grids.
Author: Stephane Thanassekos [aut, cre], Keith Reid [aut], Lucy Robinson [aut], Michael D. Sumner [ctb], Roger Bivand [ctb]
Maintainer: Stephane Thanassekos <stephane.thanassekos@ccamlr.org>

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Mon, 22 Apr 2024

Package VisualizeSimon2Stage updated to version 0.1.4 with previous version 0.1.3 dated 2024-03-20

Title: Visualize Simon's Two-Stage Design
Description: To visualize the probabilities of early termination, fail and success of Simon's two-stage design. To evaluate and visualize the operating characteristics of Simon's two-stage design.
Author: Tingting Zhan [aut, cre, cph]
Maintainer: Tingting Zhan <tingtingzhan@gmail.com>

Diff between VisualizeSimon2Stage versions 0.1.3 dated 2024-03-20 and 0.1.4 dated 2024-04-22

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Package soilDB updated to version 2.8.2 with previous version 2.8.1 dated 2024-01-09

Title: Soil Database Interface
Description: A collection of functions for reading soil data from U.S. Department of Agriculture Natural Resources Conservation Service (USDA-NRCS) and National Cooperative Soil Survey (NCSS) databases.
Author: Dylan Beaudette [aut], Jay Skovlin [aut], Stephen Roecker [aut], Andrew Brown [aut, cre]
Maintainer: Andrew Brown <andrew.g.brown@usda.gov>

Diff between soilDB versions 2.8.1 dated 2024-01-09 and 2.8.2 dated 2024-04-22

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Package wconf updated to version 1.1.0 with previous version 1.0.0 dated 2023-12-12

Title: Weighted Confusion Matrix
Description: Allows users to create weighted confusion matrices and accuracy metrics that help with the model selection process for classification problems, where distance from the correct category is important. The package includes several weighting schemes which can be parameterized, as well as custom configuration options. Furthermore, users can decide whether they wish to positively or negatively affect the accuracy score as a result of applying weights to the confusion matrix. Functions are included to calculate accuracy metrics for imbalanced data. Finally, 'wconf' integrates well with the 'caret' package, but it can also work standalone when provided data in matrix form. References: Kuhn, M. (2008) "Building Perspective Models in R Using the caret Package" <doi:10.18637/jss.v028.i05> Monahov, A. (2021) "Model Evaluation with Weighted Threshold Optimization (and the mewto R package)" <doi:10.2139/ssrn.3805911> Starovoitov, V., Golub, Y. (2020). New Function for Estimating Imbalanc [...truncated...]
Author: Alexandru Monahov [aut, cre, cph]
Maintainer: Alexandru Monahov <alexandru.monahov@proton.me>

Diff between wconf versions 1.0.0 dated 2023-12-12 and 1.1.0 dated 2024-04-22

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Package tidyterra updated to version 0.6.0 with previous version 0.5.2 dated 2024-01-19

Title: 'tidyverse' Methods and 'ggplot2' Helpers for 'terra' Objects
Description: Extension of the 'tidyverse' for 'SpatRaster' and 'SpatVector' objects of the 'terra' package. It includes also new 'geom_' functions that provide a convenient way of visualizing 'terra' objects with 'ggplot2'.
Author: Diego Hernangomez [aut, cre, cph] , Dewey Dunnington [ctb] , ggplot2 authors [cph]
Maintainer: Diego Hernangomez <diego.hernangomezherrero@gmail.com>

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Package text updated to version 1.2.1 with previous version 1.2.0 dated 2024-02-13

Title: Analyses of Text using Transformers Models from HuggingFace, Natural Language Processing and Machine Learning
Description: Link R with Transformers from Hugging Face to transform text variables to word embeddings; where the word embeddings are used to statistically test the mean difference between set of texts, compute semantic similarity scores between texts, predict numerical variables, and visual statistically significant words according to various dimensions etc. For more information see <https://www.r-text.org>.
Author: Oscar Kjell [aut, cre] , Salvatore Giorgi [aut] , Andrew Schwartz [aut]
Maintainer: Oscar Kjell <oscar.kjell@psy.lu.se>

Diff between text versions 1.2.0 dated 2024-02-13 and 1.2.1 dated 2024-04-22

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Package SpaTopic updated to version 1.1.0 with previous version 1.0.1 dated 2024-01-17

Title: Topic Inference to Identify Tissue Architecture in Multiplexed Images
Description: A novel spatial topic model to integrate both cell type and spatial information to identify the complex spatial tissue architecture on multiplexed tissue images without human intervention. The Package implements a collapsed Gibbs sampling algorithm for inference. 'SpaTopic' is scalable to large-scale image datasets without extracting neighborhood information for every single cell. For more details on the methodology, see <https://xiyupeng.github.io/SpaTopic/>.
Author: Xiyu Peng [aut, cre]
Maintainer: Xiyu Peng <pansypeng124@gmail.com>

Diff between SpaTopic versions 1.0.1 dated 2024-01-17 and 1.1.0 dated 2024-04-22

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Package SNSequate updated to version 1.3-5 with previous version 1.3-4 dated 2022-12-20

Title: Standard and Nonstandard Statistical Models and Methods for Test Equating
Description: Contains functions to perform various models and methods for test equating (Kolen and Brennan, 2014 <doi:10.1007/978-1-4939-0317-7> ; Gonzalez and Wiberg, 2017 <doi:10.1007/978-3-319-51824-4> ; von Davier et. al, 2004 <doi:10.1007/b97446>). It currently implements the traditional mean, linear and equipercentile equating methods. Both IRT observed-score and true-score equating are also supported, as well as the mean-mean, mean-sigma, Haebara and Stocking-Lord IRT linking methods. It also supports newest methods such that local equating, kernel equating (using Gaussian, logistic, Epanechnikov, uniform and adaptive kernels) with presmoothing, and IRT parameter linking methods based on asymmetric item characteristic functions. Functions to obtain both standard error of equating (SEE) and standard error of equating differences between two equating functions (SEED) are also implemented for the kernel method of equating.
Author: Jorge Gonzalez [cre, aut], Daniel Leon Acuna [ctb]
Maintainer: Jorge Gonzalez <jorge.gonzalez@mat.uc.cl>

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Package shinylight updated to version 1.2 with previous version 1.1.2 dated 2022-11-30

Title: Web Interface to 'R' Functions
Description: Web front end for your 'R' functions producing plots or tables. If you have a function or set of related functions, you can make them available over the internet through a web browser. This is the same motivation as the 'shiny' package, but note that the development of 'shinylight' is not in any way linked to that of 'shiny' (beyond the use of the 'httpuv' package). You might prefer 'shinylight' to 'shiny' if you want a lighter weight deployment with easier horizontal scaling, or if you want to develop your front end yourself in JavaScript and HTML just using a lightweight remote procedure call interface to your R code on the server.
Author: Pieter Vermeesch [aut], Tim Band [aut, cre]
Maintainer: Tim Band <t.band@ucl.ac.uk>

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Package ruijter updated to version 0.1.3 with previous version 0.1.2 dated 2023-02-08

Title: Technical Data Sets by Ruijter et al. (2013)
Description: The real-time quantitative polymerase chain reaction (qPCR) technical data sets by Ruijter et al. (2013) <doi:10.1016/j.ymeth.2012.08.011>: (i) the four-point 10-fold dilution series; (ii) 380 replicates; and (iii) the competimer data set. These three data sets can be used to benchmark qPCR methods. Original data set is available at <https://medischebiologie.nl/wp-content/uploads/2019/02/qpcrdatamethods.zip>. This package fixes incorrect annotations in the original data sets.
Author: Ramiro Magno [aut, cre] , Pattern Institute [cph, fnd]
Maintainer: Ramiro Magno <rmagno@pattern.institute>

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Package vermeulen updated to version 0.1.2 with previous version 0.1.1 dated 2022-11-10

Title: Biomarker Data Set by Vermeulen et al. (2009)
Description: The biomarker data set by Vermeulen et al. (2009) <doi:10.1016/S1470-2045(09)70154-8> is provided. The data source, however, is by Ruijter et al. (2013) <doi:10.1016/j.ymeth.2012.08.011>. The original data set may be downloaded from <https://medischebiologie.nl/wp-content/uploads/2019/02/qpcrdatamethods.zip>. This data set is for a real-time quantitative polymerase chain reaction (PCR) experiment that comprises the raw fluorescence data of 24,576 amplification curves. This data set comprises 59 genes of interest and 5 reference genes. Each gene was assessed on 366 neuroblastoma complementary DNA (cDNA) samples and on 18 standard dilution series samples (10-fold 5-point dilution series x 3 replicates + no template controls (NTC) x 3 replicates).
Author: Ramiro Magno [aut, cre] , Pattern Institute [cph, fnd]
Maintainer: Ramiro Magno <rmagno@pattern.institute>

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Package rutledge updated to version 0.1.1 with previous version 0.1.0 dated 2023-02-27

Title: Real-Time PCR Data Sets by Rutledge et al. (2004)
Description: Real-time quantitative polymerase chain reaction (qPCR) data by Rutledge et al. (2004) <doi:10.1093/nar/gnh177> in tidy format. The data comprises a six-point, ten-fold dilution series, repeated in five independent runs, for two different amplicons. In each run, each standard concentration is replicated four times. For the original raw data file see the Supplementary Data section: <https://academic.oup.com/nar/article/32/22/e178/2375678#supplementary-data>.
Author: Ramiro Magno [aut, cre] , Pattern Institute [cph, fnd]
Maintainer: Ramiro Magno <rmagno@pattern.institute>

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Package RivRetrieve updated to version 0.1.5 with previous version 0.1.4 dated 2024-03-02

Title: Retrieve Global River Gauge Data
Description: Provides access to global river gauge data from a variety of national-level river agencies. The package interfaces with the national-level agency websites to provide access to river gauge locations, river discharge, and river stage. Currently, the package is available for the following countries: Australia, Brazil, Canada, Chile, France, Japan, South Africa, the United Kingdom, and the United States.
Author: Ryan Riggs [aut, cre] , Simon Moulds [aut] , Michel Wortmann [aut] , Louise Slater [aut] , George Allen [aut]
Maintainer: Ryan Riggs <ryanriggs7@gmail.com>

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Package reticulate updated to version 1.36.1 with previous version 1.36.0 dated 2024-04-15

Title: Interface to 'Python'
Description: Interface to 'Python' modules, classes, and functions. When calling into 'Python', R data types are automatically converted to their equivalent 'Python' types. When values are returned from 'Python' to R they are converted back to R types. Compatible with all versions of 'Python' >= 2.7.
Author: Tomasz Kalinowski [ctb, cre], Kevin Ushey [aut], JJ Allaire [aut], RStudio [cph, fnd], Yuan Tang [aut, cph] , Dirk Eddelbuettel [ctb, cph], Bryan Lewis [ctb, cph], Sigrid Keydana [ctb], Ryan Hafen [ctb, cph], Marcus Geelnard [ctb, cph]
Maintainer: Tomasz Kalinowski <tomasz@posit.co>

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Package batsch updated to version 0.1.1 with previous version 0.1.0 dated 2023-02-14

Title: Real-Time PCR Data Sets by Batsch et al. (2008)
Description: Real-time quantitative polymerase chain reaction (qPCR) data sets by Batsch et al. (2008) <doi:10.1186/1471-2105-9-95>. This package provides five data sets, one for each PCR target: (i) rat SLC6A14, (ii) human SLC22A13, (iii) pig EMT, (iv) chicken ETT, and (v) human GAPDH. Each data set comprises a five-point, four-fold dilution series. For each concentration there are three replicates. Each amplification curve is 45 cycles long. Original raw data file: <https://static-content.springer.com/esm/art%3A10.1186%2F1471-2105-9-95/MediaObjects/12859_2007_2080_MOESM5_ESM.xls>.
Author: Ramiro Magno [aut, cre] , Pattern Institute [cph, fnd]
Maintainer: Ramiro Magno <rmagno@pattern.institute>

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Package EGAnet updated to version 2.0.6 with previous version 2.0.5 dated 2024-03-15

Title: Exploratory Graph Analysis – a Framework for Estimating the Number of Dimensions in Multivariate Data using Network Psychometrics
Description: Implements the Exploratory Graph Analysis (EGA) framework for dimensionality and psychometric assessment. EGA estimates the number of dimensions in psychological data using network estimation methods and community detection algorithms. A bootstrap method is provided to assess the stability of dimensions and items. Fit is evaluated using the Entropy Fit family of indices. Unique Variable Analysis evaluates the extent to which items are locally dependent (or redundant). Network loadings provide similar information to factor loadings and can be used to compute network scores. A bootstrap and permutation approach are available to assess configural and metric invariance. Hierarchical structures can be detected using Hierarchical EGA. Time series and intensive longitudinal data can be analyzed using Dynamic EGA, supporting individual, group, and population level assessments.
Author: Hudson Golino [aut, cre] , Alexander Christensen [aut] , Robert Moulder [ctb] , Luis E. Garrido [ctb] , Laura Jamison [ctb] , Dingjing Shi [ctb]
Maintainer: Hudson Golino <hfg9s@virginia.edu>

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Package WVPlots updated to version 1.3.8 with previous version 1.3.7 dated 2023-08-19

Title: Common Plots for Analysis
Description: Select data analysis plots, under a standardized calling interface implemented on top of 'ggplot2' and 'plotly'. Plots of interest include: 'ROC', gain curve, scatter plot with marginal distributions, conditioned scatter plot with marginal densities, box and stem with matching theoretical distribution, and density with matching theoretical distribution.
Author: John Mount [aut, cre], Nina Zumel [aut], Win-Vector LLC [cph]
Maintainer: John Mount <jmount@win-vector.com>

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Package plsVarSel updated to version 0.9.11 with previous version 0.9.10 dated 2023-01-12

Title: Variable Selection in Partial Least Squares
Description: Interfaces and methods for variable selection in Partial Least Squares. The methods include filter methods, wrapper methods and embedded methods. Both regression and classification is supported.
Author: Kristian Hovde Liland [aut, cre] , Tahir Mehmood [ctb], Solve Saeboe [ctb]
Maintainer: Kristian Hovde Liland <kristian.liland@nmbu.no>

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Package lares updated to version 5.2.7 with previous version 5.2.5 dated 2024-01-22

Title: Analytics & Machine Learning Sidekick
Description: Auxiliary package for better/faster analytics, visualization, data mining, and machine learning tasks. With a wide variety of family functions, like Machine Learning, Data Wrangling, Exploratory, API, and Scrapper, it helps the analyst or data scientist to get quick and robust results, without the need of repetitive coding or extensive R programming skills.
Author: Bernardo Lares [aut, cre]
Maintainer: Bernardo Lares <laresbernardo@gmail.com>

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Package gtable updated to version 0.3.5 with previous version 0.3.4 dated 2023-08-21

Title: Arrange 'Grobs' in Tables
Description: Tools to make it easier to work with "tables" of 'grobs'. The 'gtable' package defines a 'gtable' grob class that specifies a grid along with a list of grobs and their placement in the grid. Further the package makes it easy to manipulate and combine 'gtable' objects so that complex compositions can be built up sequentially.
Author: Hadley Wickham [aut], Thomas Lin Pedersen [aut, cre], Posit Software, PBC [cph, fnd]
Maintainer: Thomas Lin Pedersen <thomas.pedersen@posit.co>

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Package BayesMallows updated to version 2.2.1 with previous version 2.2.0 dated 2024-04-19

Title: Bayesian Preference Learning with the Mallows Rank Model
Description: An implementation of the Bayesian version of the Mallows rank model (Vitelli et al., Journal of Machine Learning Research, 2018 <https://jmlr.org/papers/v18/15-481.html>; Crispino et al., Annals of Applied Statistics, 2019 <doi:10.1214/18-AOAS1203>; Sorensen et al., R Journal, 2020 <doi:10.32614/RJ-2020-026>; Stein, PhD Thesis, 2023 <https://eprints.lancs.ac.uk/id/eprint/195759>). Both Metropolis-Hastings and sequential Monte Carlo algorithms for estimating the models are available. Cayley, footrule, Hamming, Kendall, Spearman, and Ulam distances are supported in the models. The rank data to be analyzed can be in the form of complete rankings, top-k rankings, partially missing rankings, as well as consistent and inconsistent pairwise preferences. Several functions for plotting and studying the posterior distributions of parameters are provided. The package also provides functions for estimating the partition function (normalizing constant) of the Mallows rank mo [...truncated...]
Author: Oystein Sorensen [aut, cre] , Waldir Leoncio [aut], Valeria Vitelli [aut] , Marta Crispino [aut], Qinghua Liu [aut], Cristina Mollica [aut], Luca Tardella [aut], Anja Stein [aut]
Maintainer: Oystein Sorensen <oystein.sorensen.1985@gmail.com>

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Package antaresRead updated to version 2.6.1 with previous version 2.6.0 dated 2023-08-30

Title: Import, Manipulate and Explore the Results of an 'Antares' Simulation
Description: Import, manipulate and explore results generated by 'Antares', a powerful open source software developed by RTE (Réseau de Transport d’Électricité) to simulate and study electric power systems (more information about 'Antares' here : <https://antares-simulator.org/>).
Author: Tatiana Vargas [aut, cre], Jalal-Edine ZAWAM [aut], Frederic Breant [ctb], Francois Guillem [aut], Benoit Thieurmel [aut], Titouan Robert [aut], Victor Perrier [ctb], Etienne Sanchez [ctb], Assil Mansouri [ctb], Clement Berthet [ctb], Kamel Kemiha [c [...truncated...]
Maintainer: Tatiana Vargas <tatiana.vargas@rte-france.com>

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Package WorldMapR updated to version 0.1.1 with previous version 0.1.0 dated 2024-02-13

Title: Worldwide or Coordinates-Based Heat Maps
Description: Easily plot heat maps of the world, based on continuous or categorical data. Country labels can also be added to the map.
Author: Luigi Annicchiarico [cre, aut]
Maintainer: Luigi Annicchiarico <luigi.annic@gmail.com>

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Package tidyBdE updated to version 0.3.6 with previous version 0.3.5 dated 2024-01-29

Title: Download Data from Bank of Spain
Description: Tools to download data series from 'Banco de España' ('BdE') on 'tibble' format. 'Banco de España' is the national central bank and, within the framework of the Single Supervisory Mechanism ('SSM'), the supervisor of the Spanish banking system along with the European Central Bank. This package is in no way sponsored endorsed or administered by 'Banco de España'.
Author: Diego H. Herrero [aut, cre, cph]
Maintainer: Diego H. Herrero <dev.dieghernan@gmail.com>

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Package cheapr updated to version 0.9.0 with previous version 0.8.0 dated 2024-04-12

Title: Simple Functions to Save Time and Memory
Description: Fast and memory-efficient (or 'cheap') tools to facilitate efficient programming, saving time and memory. It aims to provide 'cheaper' alternatives to common base R functions, as well as some additional functions.
Author: Nick Christofides [aut, cre]
Maintainer: Nick Christofides <nick.christofides.r@gmail.com>

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Package valr updated to version 0.8.1 with previous version 0.8.0 dated 2024-04-04

Title: Genome Interval Arithmetic
Description: Read and manipulate genome intervals and signals. Provides functionality similar to command-line tool suites within R, enabling interactive analysis and visualization of genome-scale data. Riemondy et al. (2017) <doi:10.12688/f1000research.11997.1>.
Author: Jay Hesselberth [aut] , Kent Riemondy [aut, cre] , RNA Bioscience Initiative [fnd, cph]
Maintainer: Kent Riemondy <kent.riemondy@cuanschutz.edu>

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Package atime updated to version 2024.4.17 with previous version 2024.4.12 dated 2024-04-13

Title: Asymptotic Timing
Description: Computing and visualizing comparative asymptotic timings of different algorithms and code versions. Also includes functionality for comparing empirical timings with expected references such as linear or quadratic, <https://en.wikipedia.org/wiki/Asymptotic_computational_complexity> Also includes functionality for measuring asymptotic memory and other quantities.
Author: Toby Hocking [aut, cre]
Maintainer: Toby Hocking <toby.hocking@r-project.org>

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Package xlcharts updated to version 0.0.2 with previous version 0.0.1 dated 2024-04-18

Title: Create Native 'Excel' Charts and Work with Microsoft 'Excel' Files
Description: An R interface to the 'OpenPyXL' 'Python' library to create native 'Excel' charts and work with Microsoft 'Excel' files.
Author: Felix Luginbuhl [aut, cre, cph] , Eric Gazoni [ctb, cph] ), Charlie Clark [ctb, cph] ), openpyxl authors [ctb, cph] )
Maintainer: Felix Luginbuhl <felix.luginbuhl@protonmail.ch>

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Package rocbc updated to version 3.1.0 with previous version 3.0.0 dated 2024-03-25

Title: Statistical Inference for Box-Cox Based Receiver Operating Characteristic Curves
Description: Generation of Box-Cox based ROC curves and several aspects of inferences and hypothesis testing. Can be used when inferences for one biomarker (Bantis LE, Nakas CT, Reiser B. (2018)<doi:10.1002/bimj.201700107>) are of interest or when comparisons of two correlated biomarkers (Bantis LE, Nakas CT, Reiser B. (2021)<doi:10.1002/bimj.202000128>) are of interest. Provides inferences and comparisons around the AUC, the Youden index, the sensitivity at a given specificity level (and vice versa), the optimal operating point of the ROC curve (in the Youden sense), and the Youden based cutoff.
Author: Leonidas Bantis [aut], Benjamin Brewer [cre, ctb], Christos Nakas [ctb], Benjamin Reiser [ctb]
Maintainer: Benjamin Brewer <tennisbenj@gmail.com>

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Package nimbleAPT updated to version 1.0.5 with previous version 1.0.4 dated 2021-11-22

Title: Adaptive Parallel Tempering for 'NIMBLE'
Description: Functions for adaptive parallel tempering (APT) with NIMBLE models. Adapted from 'Lacki' & 'Miasojedow' (2016) <DOI:10.1007/s11222-015-9579-0> and 'Miasojedow, Moulines and Vihola' (2013) <DOI:10.1080/10618600.2013.778779>.
Author: David Pleydell [aut, cre, cph] , Daniel Turek [cph] , Perry de Valpine [cph] , Christopher Paciorek [cph] , Nick Michaud [cph]
Maintainer: David Pleydell <david.pleydell@inrae.fr>

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Package evreg updated to version 1.0.4 with previous version 1.0.3 dated 2023-11-09

Title: Evidential Regression
Description: An implementation of the 'Evidential Neural Network for Regression' model recently introduced in Denoeux (2023) <doi:10.1109/TFUZZ.2023.3268200>. In this model, prediction uncertainty is quantified by Gaussian random fuzzy numbers as introduced in Denoeux (2023) <doi:10.1016/j.fss.2022.06.004>. The package contains functions for training the network, tuning hyperparameters by cross-validation or the hold-out method, and making predictions. It also contains utilities for making calculations with Gaussian random fuzzy numbers (such as, e.g., computing the degrees of belief and plausibility of an interval, or combining Gaussian random fuzzy numbers).
Author: Thierry Denoeux [aut, cre]
Maintainer: Thierry Denoeux <tdenoeux@utc.fr>

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Package diseasystore updated to version 0.2.1 with previous version 0.2.0 dated 2024-03-20

Title: Feature Stores for the 'diseasy' Framework
Description: Simple feature stores and tools for creating personalised feature stores. 'diseasystore' powers feature stores which can automatically link and aggregate features to a given stratification level. These feature stores are automatically time-versioned (powered by the 'SCDB' package) and allows you to easily and dynamically compute features as part of your continuous integration.
Author: Rasmus Skytte Randloev [aut, cre] , Marcus Munch Gruenewald [ctb] , Kaare Graesboell [rev] , Kasper Schou Telkamp [rev] , Lasse Engbo Christiansen [rev] , Sofia Myrup Otero [rev], Statens Serum Institut, SSI [cph, fnd]
Maintainer: Rasmus Skytte Randloev <rske@ssi.dk>

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Package sgboost updated to version 0.1.2 with previous version 0.1.0 dated 2024-04-11

Title: Sparse-Group Boosting
Description: Sparse-group boosting to be used in conjunction with the 'mboost' for modeling grouped data. Applicable to all sparse-group lasso type problems where within-group and between-group sparsity is desired. Interprets and visualizes individual variables and groups.
Author: Fabian Obster [aut, cre, cph]
Maintainer: Fabian Obster <fabian.obster@unibw.de>

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Package RainfallErosivityFactor updated to version 1.0.0 with previous version 0.1.0 dated 2018-11-18

Title: The Rainfall-Runoff Erosivity Factor
Description: Determination of rainfall-runoff erosivity factor.
Author: Dione Pereira Cardoso [aut, cre], Edilson Marcelino Silva [aut], Paulo Cesar Ossani [aut], Marx Leandro Naves Silva [ctb], Joel Augusto Muniz [ctb], Daniel Furtado Ferreira [ctb], Junior Cesar Avanzi [ctb]
Maintainer: Dione Pereira Cardoso <cardoso.dione@gmail.com>

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Package lrstat updated to version 0.2.5 with previous version 0.2.4 dated 2024-03-19

Title: Power and Sample Size Calculation for Non-Proportional Hazards and Beyond
Description: Performs power and sample size calculation for non-proportional hazards model using the Fleming-Harrington family of weighted log-rank tests. The sequentially calculated log-rank test score statistics are assumed to have independent increments as characterized in Anastasios A. Tsiatis (1982) <doi:10.1080/01621459.1982.10477898>. The mean and variance of log-rank test score statistics are calculated based on Kaifeng Lu (2021) <doi:10.1002/pst.2069>. The boundary crossing probabilities are calculated using the recursive integration algorithm described in Christopher Jennison and Bruce W. Turnbull (2000, ISBN:0849303168). The package can also be used for continuous, binary, and count data. For continuous data, it can handle missing data through mixed-model for repeated measures (MMRM). In crossover designs, it can estimate direct treatment effects while accounting for carryover effects. For binary data, it can design Simon's 2-stage, modified toxicity probability-2 (mTPI-2), a [...truncated...]
Author: Kaifeng Lu
Maintainer: Kaifeng Lu <kaifenglu@gmail.com>

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Package ern updated to version 2.0.0 with previous version 1.3.1 dated 2024-01-29

Title: Effective Reproduction Number Estimation
Description: Estimate the effective reproduction number from wastewater and clinical data sources.
Author: David Champredon [aut, cre] , Warsame Yusuf [aut] , Irena Papst [aut]
Maintainer: David Champredon <david.champredon@canada.ca>

Diff between ern versions 1.3.1 dated 2024-01-29 and 2.0.0 dated 2024-04-22

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Package LipidomicsR updated to version 0.3.6 with previous version 0.1.6 dated 2024-03-16

Title: Elegant Tools for Processing and Visualization of Lipidomics Data
Description: An elegant tool for processing and visualizing lipidomics data generated by mass spectrometry. 'LipidomicsR' simplifies channel and replicate handling while providing thorough lipid species annotation. Its visualization capabilities encompass principal components analysis plots, heatmaps, volcano plots, and radar plots, enabling concise data summarization and quality assessment. Additionally, it can generate bar plots and line plots to visualize the abundance of each lipid species.
Author: Mingshi Li [aut, com], Hengyu Zhu [aut, cre]
Maintainer: Hengyu Zhu <hengyu.21@intl.zju.edu.cn>

Diff between LipidomicsR versions 0.1.6 dated 2024-03-16 and 0.3.6 dated 2024-04-22

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Package fabletools updated to version 0.4.2 with previous version 0.4.1 dated 2024-03-02

Title: Core Tools for Packages in the 'fable' Framework
Description: Provides tools, helpers and data structures for developing models and time series functions for 'fable' and extension packages. These tools support a consistent and tidy interface for time series modelling and analysis.
Author: Mitchell O'Hara-Wild [aut, cre] , Rob Hyndman [aut], Earo Wang [aut] , Di Cook [ctb], George Athanasopoulos [ctb], David Holt [ctb]
Maintainer: Mitchell O'Hara-Wild <mail@mitchelloharawild.com>

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Package ripc updated to version 0.3.0 with previous version 0.2.1 dated 2024-03-15

Title: Download and Tidy IPC and CH Data
Description: Utilities to access Integrated Food Security Phase Classification (IPC) and Cadre Harmonisé (CH) food security data. Wrapper functions are available for all of the 'IPC-CH' Public API (<https://docs.api.ipcinfo.org>) simplified and advanced endpoints to easily download the data in a clean and tidy format.
Author: Seth Caldwell [aut, cre, cph]
Maintainer: Seth Caldwell <caldwellst@gmail.com>

Diff between ripc versions 0.2.1 dated 2024-03-15 and 0.3.0 dated 2024-04-22

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Package memoiR updated to version 1.2-9 with previous version 1.2-7 dated 2024-02-26

Title: R Markdown and Bookdown Templates to Publish Documents
Description: Producing high-quality documents suitable for publication directly from R is made possible by the R Markdown ecosystem. 'memoiR' makes it easy. It provides templates to knit memoirs, articles and slideshows with helpers to publish the documents on GitHub Pages and activate continuous integration.
Author: Eric Marcon [aut, cre]
Maintainer: Eric Marcon <eric.marcon@agroparistech.fr>

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Package acled.api updated to version 1.1.8 with previous version 1.1.7 dated 2024-01-10

Title: Automated Retrieval of ACLED Conflict Event Data
Description: Access and manage the application programming interface (API) of the Armed Conflict Location & Event Data Project (ACLED) at <https://acleddata.com/>. The package makes it easy to retrieve a user-defined sample (or all of the available data) of ACLED, enabling a seamless integration of regular data updates into the research work flow. It requires a minimal number of dependencies. See the package's README file for a note on replicability when drawing on ACLED data. When using this package, you acknowledge that you have read ACLED's terms and conditions of use, and that you agree with their attribution requirements.
Author: Christoph Dworschak [aut, cre] , Rob Williams [ctb]
Maintainer: Christoph Dworschak <dworschak@posteo.de>

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Package SAiVE updated to version 1.0.5 with previous version 1.0.4 dated 2024-02-07

Title: Functions Used for SAiVE Group Research, Collaborations, and Publications
Description: Holds functions developed by the University of Ottawa's SAiVE (Spatio-temporal Analysis of isotope Variations in the Environment) research group with the intention of facilitating the re-use of code, foster good code writing practices, and to allow others to benefit from the work done by the SAiVE group. Contributions are welcome via the 'GitHub' repository <https://github.com/UO-SAiVE/SAiVE> by group members as well as non-members.
Author: Ghislain de Laplante [aut, cre, cph]
Maintainer: Ghislain de Laplante <ghislain.delaplante@yukon.ca>

Diff between SAiVE versions 1.0.4 dated 2024-02-07 and 1.0.5 dated 2024-04-22

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Package rococo updated to version 1.1.8 with previous version 1.1.7 dated 2018-10-12

Title: Robust Rank Correlation Coefficient and Test
Description: Provides the robust gamma rank correlation coefficient as introduced by Bodenhofer, Krone, and Klawonn (2013) <DOI:10.1016/j.ins.2012.11.026> along with a permutation-based rank correlation test. The rank correlation coefficient and the test are explicitly designed for dealing with noisy numerical data.
Author: Martin Krone [aut], Ulrich Bodenhofer [aut,cre]
Maintainer: Ulrich Bodenhofer <ulrich@bodenhofer.com>

Diff between rococo versions 1.1.7 dated 2018-10-12 and 1.1.8 dated 2024-04-22

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Package ieugwasr updated to version 1.0.0 with previous version 0.2.2 dated 2024-03-28

Title: Interface to the 'OpenGWAS' Database API
Description: Interface to the 'OpenGWAS' database API <https://gwas-api.mrcieu.ac.uk/>. Includes a wrapper to make generic calls to the API, plus convenience functions for specific queries.
Author: Gibran Hemani [aut, cre, cph] , Ben Elsworth [aut] , Tom Palmer [aut] , Rita Rasteiro [aut]
Maintainer: Gibran Hemani <g.hemani@bristol.ac.uk>

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More information about ieugwasr at CRAN
Permanent link

Package colorscience updated to version 1.0.9 with previous version 1.0.8 dated 2019-10-29

Title: Color Science Methods and Data
Description: Methods and data for color science - color conversions by observer, illuminant, and gamma. Color matching functions and chromaticity diagrams. Color indices, color differences, and spectral data conversion/analysis. This package is deprecated and will someday be removed; for reasons and details please see the README file.
Author: Jose Gama [aut], Glenn Davis [aut, cre]
Maintainer: Glenn Davis <gdavis@gluonics.com>

Diff between colorscience versions 1.0.8 dated 2019-10-29 and 1.0.9 dated 2024-04-22

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Package BMRMM updated to version 1.0.1 with previous version 1.0.0 dated 2023-06-19

Title: An Implementation of the Bayesian Markov (Renewal) Mixed Models
Description: The Bayesian Markov renewal mixed models take sequentially observed categorical data with continuous duration times, being either state duration or inter-state duration. These models comprehensively analyze the stochastic dynamics of both state transitions and duration times under the influence of multiple exogenous factors and random individual effect. The default setting flexibly models the transition probabilities using Dirichlet mixtures and the duration times using gamma mixtures. It also provides the flexibility of modeling the categorical sequences using Bayesian Markov mixed models alone, either ignoring the duration times altogether or dividing duration time into multiples of an additional category in the sequence by a user-specific unit. The package allows extensive inference of the state transition probabilities and the duration times as well as relevant plots and graphs. It also includes a synthetic data set to demonstrate the desired format of input data set and the utilit [...truncated...]
Author: Yutong Wu [aut, cre], Abhra Sarkar [aut]
Maintainer: Yutong Wu <yutong.wu@utexas.edu>

Diff between BMRMM versions 1.0.0 dated 2023-06-19 and 1.0.1 dated 2024-04-22

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Sun, 21 Apr 2024

Package MSclust updated to version 1.0.4 with previous version 1.0.3 dated 2023-05-04

Title: Multiple-Scaled Clustering
Description: Model based clustering using the multivariate multiple Scaled t (MST) and multivariate multiple scaled contaminated normal (MSCN) distributions. The MST is an extension of the multivariate Student-t distribution to include flexible tail behaviors, Forbes, F. & Wraith, D. (2014) <doi:10.1007/s11222-013-9414-4>. The MSCN represents a heavy-tailed generalization of the multivariate normal (MN) distribution to model elliptical contoured scatters in the presence of mild outliers (also referred to as "bad" points) and automatically detect bad points, Punzo, A. & Tortora, C. (2021) <doi:10.1177/1471082X19890935>.
Author: Cristina Tortora [aut, cre, cph] , Antonio Punzo [aut] , Louis Tran [aut]
Maintainer: Cristina Tortora <grikris1@gmail.com>

Diff between MSclust versions 1.0.3 dated 2023-05-04 and 1.0.4 dated 2024-04-21

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Package rEMM updated to version 1.2.1 with previous version 1.2.0 dated 2022-06-25

Title: Extensible Markov Model for Modelling Temporal Relationships Between Clusters
Description: Implements TRACDS (Temporal Relationships between Clusters for Data Streams), a generalization of Extensible Markov Model (EMM). TRACDS adds a temporal or order model to data stream clustering by superimposing a dynamically adapting Markov Chain. Also provides an implementation of EMM (TRACDS on top of tNN data stream clustering). Development of this package was supported in part by NSF IIS-0948893 and R21HG005912 from the National Human Genome Research Institute. Hahsler and Dunham (2010) <doi:10.18637/jss.v035.i05>.
Author: Michael Hahsler [aut, cre, cph] , Margaret H. Dunham [ctb]
Maintainer: Michael Hahsler <mhahsler@lyle.smu.edu>

Diff between rEMM versions 1.2.0 dated 2022-06-25 and 1.2.1 dated 2024-04-21

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More information about rEMM at CRAN
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Package stream updated to version 2.0-2 with previous version 2.0-1 dated 2023-02-28

Title: Infrastructure for Data Stream Mining
Description: A framework for data stream modeling and associated data mining tasks such as clustering and classification. The development of this package was supported in part by NSF IIS-0948893, NSF CMMI 1728612, and NIH R21HG005912. Hahsler et al (2017) <doi:10.18637/jss.v076.i14>.
Author: Michael Hahsler [aut, cre, cph] , Matthew Bolanos [ctb], John Forrest [ctb], Matthias Carnein [ctb], Dennis Assenmacher [ctb], Dalibor Krleza [ctb]
Maintainer: Michael Hahsler <mhahsler@lyle.smu.edu>

Diff between stream versions 2.0-1 dated 2023-02-28 and 2.0-2 dated 2024-04-21

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More information about stream at CRAN
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Package uwot updated to version 0.2.2 with previous version 0.2.1 dated 2024-04-15

Title: The Uniform Manifold Approximation and Projection (UMAP) Method for Dimensionality Reduction
Description: An implementation of the Uniform Manifold Approximation and Projection dimensionality reduction by McInnes et al. (2018) <doi:10.48550/arXiv.1802.03426>. It also provides means to transform new data and to carry out supervised dimensionality reduction. An implementation of the related LargeVis method of Tang et al. (2016) <doi:10.48550/arXiv.1602.00370> is also provided. This is a complete re-implementation in R (and C++, via the 'Rcpp' package): no Python installation is required. See the uwot website (<https://github.com/jlmelville/uwot>) for more documentation and examples.
Author: James Melville [aut, cre, cph], Aaron Lun [ctb], Mohamed Nadhir Djekidel [ctb], Yuhan Hao [ctb], Dirk Eddelbuettel [ctb]
Maintainer: James Melville <jlmelville@gmail.com>

Diff between uwot versions 0.2.1 dated 2024-04-15 and 0.2.2 dated 2024-04-21

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More information about uwot at CRAN
Permanent link

Package openssl updated to version 2.1.2 with previous version 2.1.1 dated 2023-09-25

Title: Toolkit for Encryption, Signatures and Certificates Based on OpenSSL
Description: Bindings to OpenSSL libssl and libcrypto, plus custom SSH key parsers. Supports RSA, DSA and EC curves P-256, P-384, P-521, and curve25519. Cryptographic signatures can either be created and verified manually or via x509 certificates. AES can be used in cbc, ctr or gcm mode for symmetric encryption; RSA for asymmetric (public key) encryption or EC for Diffie Hellman. High-level envelope functions combine RSA and AES for encrypting arbitrary sized data. Other utilities include key generators, hash functions (md5, sha1, sha256, etc), base64 encoder, a secure random number generator, and 'bignum' math methods for manually performing crypto calculations on large multibyte integers.
Author: Jeroen Ooms [aut, cre] , Oliver Keyes [ctb]
Maintainer: Jeroen Ooms <jeroen@berkeley.edu>

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Permanent link

Package INLAspacetime updated to version 0.1.8 with previous version 0.1.7 dated 2023-08-27

Title: Spatial and Spatio-Temporal Models using 'INLA'
Description: Prepare objects to implement models over spatial and spacetime domains with the 'INLA' package (<https://www.r-inla.org>). These objects contain data to for the 'cgeneric' interface in 'INLA', enabling fast parallel computations. We implemented the spatial barrier model, see Bakka et. al. (2019) <doi:10.1016/j.spasta.2019.01.002>, and some of the spatio-temporal models in Lindgren et. al. (2023) <doi:10.48550/arXiv.2006.04917>. Details are provided in the available vignettes and from the URL bellow.
Author: Elias Teixeira Krainski [cre, aut, cph] , Finn Lindgren [aut] , Haavard Rue [aut]
Maintainer: Elias Teixeira Krainski <eliaskrainski@gmail.com>

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Permanent link

Package glmnetr updated to version 0.4-6 with previous version 0.4-5 dated 2024-04-19

Title: Nested Cross Validation for the Relaxed Lasso and Other Machine Learning Models
Description: Cross validation informed Relaxed LASSO, Artificial Neural Network (ANN), gradient boosting machine ('xgboost'), Random Forest ('RandomForestSRC'), Recursive Partitioning ('RPART') or step wise regression models are fit. Nested cross validation (or analogous for the random forest) is used to estimate and compare performances between these models with results presented in tabular or graphical means. Calibration plots can also be generated, again based upon (nested) cross validation. For some datasets, for example when the design matrix is not of full rank, 'glmnet' may have very long run times when fitting the relaxed lasso model, from our experience when fitting Cox models on data with many predictors and many patients, making it difficult to get solutions from either glmnet() or cv.glmnet(). This may be remedied with the 'path=TRUE' options when calling glmnet() and cv.glmnet(). Within the glmnetr package the approach of path=TRUE is taken by default. When fitting not a relaxed la [...truncated...]
Author: Walter K Kremers [aut, cre] , Nicholas B Larson [ctb]
Maintainer: Walter K Kremers <kremers.walter@mayo.edu>

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Package gdi updated to version 1.6.0 with previous version 1.5.4 dated 2023-09-07

Title: Volumetric Analysis using Graphic Double Integration
Description: Tools implementing an automated version of the graphic double integration technique (GDI) for volume implementation, and some other related utilities for paleontological image-analysis. GDI was first employed by Jerison (1973) <ISBN:9780323141086> and Hurlburt (1999) <doi:10.1080/02724634.1999.10011145> and is primarily used for volume or mass estimation of (extinct) animals. The package 'gdi' aims to make this technique as convenient and versatile as possible. The core functions of 'gdi' provide utilities for automatically measuring diameters from digital silhouettes provided as image files and calculating volume via graphic double integration with simple elliptical, superelliptical (following Motani 2001 <doi:10.1666/0094-8373(2001)027%3C0735:EBMFST%3E2.0.CO;2>) or complex cross-sectional models. Additionally, the package provides functions for estimating the center of mass position (COM), the moment of inertia (I) for 3D shapes and the second moment of area (Ix, Iy [...truncated...]
Author: Darius Nau [aut, cre]
Maintainer: Darius Nau <dariusnau@gmx.at>

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Package flps updated to version 1.1.0 with previous version 1.0.0 dated 2023-11-02

Title: Fully-Latent Principal Stratification
Description: Simulation and analysis of Fully-Latent Principal Stratification (FLPS) with measurement models. Lee, Adam, Kang, & Whittaker (2023). <doi:10.1007/978-3-031-27781-8_25>. This package is supported by the Institute of Education Sciences, U.S. Department of Education, through Grant R305D210036.
Author: Sooyong Lee [aut, cre], Adam Sales [aut], Hyeon-Ah Kang [aut], Tiffany Whittaker [aut]
Maintainer: Sooyong Lee <sooyongl09@gmail.com>

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Package flexsurv updated to version 2.3 with previous version 2.2.2 dated 2023-02-01

Title: Flexible Parametric Survival and Multi-State Models
Description: Flexible parametric models for time-to-event data, including the Royston-Parmar spline model, generalized gamma and generalized F distributions. Any user-defined parametric distribution can be fitted, given at least an R function defining the probability density or hazard. There are also tools for fitting and predicting from fully parametric multi-state models, based on either cause-specific hazards or mixture models.
Author: Christopher Jackson [aut, cre], Paul Metcalfe [ctb], Jordan Amdahl [ctb], Matthew T. Warkentin [ctb], Michael Sweeting [ctb], Kevin Kunzmann [ctb]
Maintainer: Christopher Jackson <chris.jackson@mrc-bsu.cam.ac.uk>

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Package CRE updated to version 0.2.6 with previous version 0.2.5 dated 2023-12-06

Title: Interpretable Discovery and Inference of Heterogeneous Treatment Effects
Description: Provides a new method for interpretable heterogeneous treatment effects characterization in terms of decision rules via an extensive exploration of heterogeneity patterns by an ensemble-of-trees approach, enforcing high stability in the discovery. It relies on a two-stage pseudo-outcome regression, and it is supported by theoretical convergence guarantees. Bargagli-Stoffi, F. J., Cadei, R., Lee, K., & Dominici, F. (2023) Causal rule ensemble: Interpretable Discovery and Inference of Heterogeneous Treatment Effects. arXiv preprint <doi:10.48550/arXiv.2009.09036>.
Author: Naeem Khoshnevis [aut, cre] , Daniela Maria Garcia [aut] , Riccardo Cadei [aut] , Kwonsang Lee [aut] , Falco Joannes Bargagli Stoffi [aut]
Maintainer: Naeem Khoshnevis <nkhoshnevis@g.harvard.edu>

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Package allometric updated to version 2.3.0 with previous version 2.1.0 dated 2023-11-07

Title: Structured Allometric Models for Trees
Description: Access allometric models used in forest resource analysis, such as volume equations, taper equations, biomass models, among many others. Users are able to efficiently find and select allometric models suitable for their project area and use them in analysis. Additionally, 'allometric' provides a structured framework for adding new models to an open-source models repository.
Author: Bryce Frank [aut, cre] , Francisco Mauro [aut] , Elijah Allensworth [aut]
Maintainer: Bryce Frank <bfrank70@gmail.com>

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Package rtpcr updated to version 1.0.5 with previous version 1.0.4 dated 2024-04-20

Title: qPCR Data Analysis
Description: Various methods are employed for statistical analysis and graphical presentation of real-time PCR (quantitative PCR or qPCR) data. 'rtpcr' handles amplification efficiency calculation, statistical analysis and graphical representation of real-time PCR data based on up to two reference genes. By accounting for amplification efficiency values, 'rtpcr' was developed using a general calculation method described by Ganger et al. (2017) <doi:10.1186/s12859-017-1949-5> and Taylor et al. (2019) <doi:10.1016/j.tibtech.2018.12.002>, covering both the Livak and Pfaffl methods. Based on the experimental conditions, the functions of the 'rtpcr' package use t-test (for experiments with a two-level factor) or analysis of variance (for cases where more than two levels or factors exist) to calculate the fold change or relative expression. The functions also provide standard deviations and confidence limits for means and apply statistical mean comparisons. To facilitate using 'rtpcr', diffe [...truncated...]
Author: Ghader Mirzaghaderi [aut, cre, cph]
Maintainer: Ghader Mirzaghaderi <gh.mirzaghaderi@uok.ac.ir>

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Package linelist updated to version 1.1.3 with previous version 1.1.2 dated 2024-04-19

Title: Tagging and Validating Epidemiological Data
Description: Provides tools to help storing and handling case line list data. The 'linelist' class adds a tagging system to classical 'data.frame' objects to identify key epidemiological data such as dates of symptom onset, epidemiological case definition, age, gender or disease outcome. Once tagged, these variables can be seamlessly used in downstream analyses, making data pipelines more robust and reliable.
Author: Hugo Gruson [aut, cre] , Thibaut Jombart [aut, ccp], Tim Taylor [ctb], Chris Hartgerink [rev]
Maintainer: Hugo Gruson <hugo@data.org>

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Package DeclareDesign updated to version 1.0.10 with previous version 1.0.8 dated 2024-03-07

Title: Declare and Diagnose Research Designs
Description: Researchers can characterize and learn about the properties of research designs before implementation using `DeclareDesign`. Ex ante declaration and diagnosis of designs can help researchers clarify the strengths and limitations of their designs and to improve their properties, and can help readers evaluate a research strategy prior to implementation and without access to results. It can also make it easier for designs to be shared, replicated, and critiqued.
Author: Graeme Blair [aut, cre] , Jasper Cooper [aut] , Alexander Coppock [aut] , Macartan Humphreys [aut] , Neal Fultz [aut]
Maintainer: Graeme Blair <graeme.blair@gmail.com>

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Package baRulho updated to version 2.1.0 with previous version 1.0.6 dated 2022-03-01

Title: Quantifying (Animal) Sound Degradation
Description: Intended to facilitate acoustic analysis of (animal) sound transmission experiments, which typically aim to quantify changes in signal structure when transmitted in a given habitat by broadcasting and re-recording animal sounds at increasing distances. The package offers a workflow with functions to prepare the data set for analysis as well as to calculate and visualize several degradation metrics, including blur ratio, signal-to-noise ratio, excess attenuation and envelope correlation among others (Dabelsteen et al 1993 <doi:10.1121/1.406682>).
Author: Marcelo Araya-Salas [aut, cre] , Michael Mahoney [rev] , Dena Clink [rev]
Maintainer: Marcelo Araya-Salas <marcelo.araya@ucr.ac.cr>

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Package biglasso updated to version 1.6.0 with previous version 1.5.2 dated 2022-10-05

Title: Extending Lasso Model Fitting to Big Data
Description: Extend lasso and elastic-net model fitting for ultra high-dimensional, multi-gigabyte data sets that cannot be loaded into memory. Designed to be more memory- and computation-efficient than existing lasso-fitting packages like 'glmnet' and 'ncvreg', thus allowing the user to analyze big data analysis even on an ordinary laptop.
Author: Yaohui Zeng [aut], Chuyi Wang [aut], Tabitha Peter [aut], Patrick Breheny [aut, cre]
Maintainer: Patrick Breheny <patrick-breheny@uiowa.edu>

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Package origin updated to version 1.1.2 with previous version 1.1.1 dated 2023-09-03

Title: Explicitly Qualifying Namespaces by Automatically Adding 'pkg::' to Functions
Description: Automatically adding 'pkg::' to a function, i.e. mutate() becomes dplyr::mutate(). It is up to the user to determine which packages should be used explicitly, whether to include base R packages or use the functionality on selected text, a file, or a complete directory. User friendly logging is provided in the 'RStudio' Markers pane. Lives in the spirit of 'lintr' and 'styler'. Can also be used for checking which packages are actually used in a project.
Author: Matthias Nistler
Maintainer: Matthias Nistler <m_nistler@web.de>

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Package DanielBiostatistics10th updated to version 0.2.1 with previous version 0.2.0 dated 2024-04-11

Title: Functions for Wayne W. Daniel's Biostatistics, Tenth Edition
Description: Functions to accompany Wayne W. Daniel's Biostatistics: A Foundation for Analysis in the Health Sciences, Tenth Edition.
Author: Tingting Zhan [aut, cre, cph]
Maintainer: Tingting Zhan <tingtingzhan@gmail.com>

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Package ThomasJeffersonUniv updated to version 0.1.1 with previous version 0.1.0 dated 2022-05-18

Title: Handy Tools for TJU/TJUH Employees
Description: Functions for admin needs of employees of Thomas Jefferson University and Thomas Jefferson University Hospital, Philadelphia, PA.
Author: Tingting Zhan [aut, cre, cph]
Maintainer: Tingting Zhan <tingtingzhan@gmail.com>

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Sat, 20 Apr 2024

Package micromapST updated to version 3.0.3 with previous version 3.0.2 dated 2024-01-10

Title: Linked Micromap Plots for U. S. and Other Geographic Areas
Description: Provides the users with the ability to quickly create linked micromap plots for a collection of geographic areas. Linked micromap plots are visualizations of geo-referenced data that link statistical graphics to an organized series of small maps or graphic images. The Help description contains examples of how to use the 'micromapST' function. Contained in this package are border group datasets to support creating linked micromap plots for the 50 U.S. states and District of Columbia (51 areas), the U. S. 20 Seer Registries, the 105 counties in the state of Kansas, the 62 counties of New York, the 24 counties of Maryland, the 29 counties of Utah, the 32 administrative areas in China, the 218 administrative areas in the UK and Ireland (for testing only), the 25 districts in the city of Seoul South Korea, and the 52 counties on the Africa continent. A border group dataset contains the boundaries related to the data level areas, a second layer boundaries, a top or third layer boundary, a pa [...truncated...]
Author: Jim Pearson [aut, cre, cph], Dan Carr [aut, cph], Linda Pickle [ctb, cph]
Maintainer: Jim Pearson <jbpearson353@gmail.com>

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Package streamMOA updated to version 1.3-1 with previous version 1.3-0 dated 2022-09-03

Title: Interface for MOA Stream Clustering Algorithms
Description: Interface for data stream clustering algorithms implemented in the MOA (Massive Online Analysis) framework (Albert Bifet, Geoff Holmes, Richard Kirkby, Bernhard Pfahringer (2010). MOA: Massive Online Analysis, Journal of Machine Learning Research 11: 1601-1604).
Author: Michael Hahsler [aut, cre, cph] , John Forrest [aut, cph], Matthew Bolanos [ctb], Matthias Carnein [ctb], Dalibor Krleza [ctb]
Maintainer: Michael Hahsler <mhahsler@lyle.smu.edu>

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Package ncvreg updated to version 3.14.2 with previous version 3.14.1 dated 2023-04-25

Title: Regularization Paths for SCAD and MCP Penalized Regression Models
Description: Fits regularization paths for linear regression, GLM, and Cox regression models using lasso or nonconvex penalties, in particular the minimax concave penalty (MCP) and smoothly clipped absolute deviation (SCAD) penalty, with options for additional L2 penalties (the "elastic net" idea). Utilities for carrying out cross-validation as well as post-fitting visualization, summarization, inference, and prediction are also provided. For more information, see Breheny and Huang (2011) <doi:10.1214/10-AOAS388> or visit the ncvreg homepage <https://pbreheny.github.io/ncvreg/>.
Author: Patrick Breheny [aut, cre]
Maintainer: Patrick Breheny <patrick-breheny@uiowa.edu>

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Package sketchy updated to version 1.0.3 with previous version 1.0.2 dated 2022-02-09

Title: Create Custom Research Compendiums
Description: Provides functions to create and manage research compendiums for data analysis. Research compendiums are a standard and intuitive folder structure for organizing the digital materials of a research project, which can significantly improve reproducibility. The package offers several compendium structure options that fit different research project as well as the ability of duplicating the folder structure of existing projects or implementing custom structures. It also simplifies the use of version control.
Author: Marcelo Araya-Salas [aut, cre] , Andrea Yure Arriaga Madrigal [aut]
Maintainer: Marcelo Araya-Salas <marcelo.araya@ucr.ac.cr>

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Package ivreg updated to version 0.6-3 with previous version 0.6-2 dated 2023-03-17

Title: Instrumental-Variables Regression by '2SLS', '2SM', or '2SMM', with Diagnostics
Description: Instrumental variable estimation for linear models by two-stage least-squares (2SLS) regression or by robust-regression via M-estimation (2SM) or MM-estimation (2SMM). The main ivreg() model-fitting function is designed to provide a workflow as similar as possible to standard lm() regression. A wide range of methods is provided for fitted ivreg model objects, including extensive functionality for computing and graphing regression diagnostics in addition to other standard model tools.
Author: John Fox [aut] , Christian Kleiber [aut] , Achim Zeileis [aut, cre] , Nikolas Kuschnig [ctb] , R Core Team [ctb]
Maintainer: Achim Zeileis <Achim.Zeileis@R-project.org>

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Package tm updated to version 0.7-13 with previous version 0.7-12 dated 2024-03-11

Title: Text Mining Package
Description: A framework for text mining applications within R.
Author: Ingo Feinerer [aut, cre] , Kurt Hornik [aut] , Artifex Software, Inc. [ctb, cph]
Maintainer: Ingo Feinerer <feinerer@logic.at>

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Package selenider updated to version 0.4.0 with previous version 0.3.0 dated 2024-01-27

Title: Concise, Lazy and Reliable Wrapper for 'chromote' and 'selenium'
Description: A user-friendly wrapper for web automation, using either 'chromote' or 'selenium'. Provides a simple and consistent API to make web scraping and testing scripts easy to write and understand. Elements are lazy, and automatically wait for the website to be valid, resulting in reliable and reproducible code, with no visible impact on the experience of the programmer.
Author: Ashby Thorpe [aut, cre, cph]
Maintainer: Ashby Thorpe <ashbythorpe@gmail.com>

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Package rtpcr updated to version 1.0.4 with previous version 1.0.3 dated 2024-04-13

Title: qPCR Data Analysis
Description: Various methods are employed for statistical analysis and graphical presentation of real-time PCR (quantitative PCR or qPCR) data. 'rtpcr' handles amplification efficiency calculation, statistical analysis and graphical representation of real-time PCR data based on up to two reference genes. By accounting for amplification efficiency values, 'rtpcr' was developed using a general calculation method described by Ganger et al. (2017) <doi:10.1186/s12859-017-1949-5> and Taylor et al. (2019) <doi:10.1016/j.tibtech.2018.12.002>, covering both the Livak and Pfaffl methods. Based on the experimental conditions, the functions of the 'rtpcr' package use t-test (for experiments with a two-level factor) or analysis of variance (for cases where more than two levels or factors exist) to calculate the fold change or relative expression. The functions also provide standard deviations and confidence limits for means and apply statistical mean comparisons. To facilitate using 'rtpcr', diffe [...truncated...]
Author: Ghader Mirzaghaderi [aut, cre, cph]
Maintainer: Ghader Mirzaghaderi <gh.mirzaghaderi@uok.ac.ir>

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Package XRJulia updated to version 0.9.0.1 with previous version 0.9.0 dated 2019-05-05

Title: Structured Interface to Julia
Description: A Julia interface structured according to the general form described in package 'XR' and in the book "Extending R".
Author: John M. Chambers
Maintainer: John Chambers <jmc@r-project.org>

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Package secrdesign updated to version 2.9.1 with previous version 2.9.0 dated 2024-03-02

Title: Sampling Design for Spatially Explicit Capture-Recapture
Description: Tools for designing spatially explicit capture-recapture studies of animal populations. This is primarily a simulation manager for package 'secr'. Extensions in version 2.5.0 include costing and evaluation of detector spacing.
Author: Murray Efford [aut, cre] , Ian Durbach [ctb]
Maintainer: Murray Efford <murray.efford@otago.ac.nz>

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Package pamr updated to version 1.56.2 with previous version 1.56.1 dated 2019-04-22

Title: Pam: Prediction Analysis for Microarrays
Description: Some functions for sample classification in microarrays.
Author: T. Hastie, R. Tibshirani, Balasubramanian Narasimhan, Gil Chu
Maintainer: Rob Tibshirani <tibs@stanford.edu>

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Package GSA updated to version 1.03.3 with previous version 1.03.2 dated 2022-03-19

Title: Gene Set Analysis
Description: Gene Set Analysis.
Author: Brad Efron and R. Tibshirani
Maintainer: Rob Tibshirani <tibs@stat.stanford.edu>

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Package Factoshiny updated to version 2.6 with previous version 2.5 dated 2023-11-20

Title: Perform Factorial Analysis from 'FactoMineR' with a Shiny Application
Description: Perform factorial analysis with a menu and draw graphs interactively thanks to 'FactoMineR' and a Shiny application.
Author: Pauline Vaissie, Astrid Monge, Francois Husson
Maintainer: Francois Husson <francois.husson@institut-agro.fr>

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Package FactoMineR updated to version 2.11 with previous version 2.10 dated 2024-02-29

Title: Multivariate Exploratory Data Analysis and Data Mining
Description: Exploratory data analysis methods to summarize, visualize and describe datasets. The main principal component methods are available, those with the largest potential in terms of applications: principal component analysis (PCA) when variables are quantitative, correspondence analysis (CA) and multiple correspondence analysis (MCA) when variables are categorical, Multiple Factor Analysis when variables are structured in groups, etc. and hierarchical cluster analysis. F. Husson, S. Le and J. Pages (2017).
Author: Francois Husson, Julie Josse, Sebastien Le, Jeremy Mazet
Maintainer: Francois Husson <francois.husson@institut-agro.fr>

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Package dbparser updated to version 2.0.3 with previous version 2.0.2 dated 2024-02-16

Title: Drugs Databases Parser
Description: This tool is for parsing public drug databases such as 'DrugBank' XML database <https://go.drugbank.com/>. The parsed data are then returned in a proper 'R' object called 'dvobject'.
Author: Mohammed Ali [aut, cre], Ali Ezzat [aut], Hao Zhu [rev], Emma Mendelsohn [rev]
Maintainer: Mohammed Ali <moh_fcis@yahoo.com>

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Package keras updated to version 2.15.0 with previous version 2.13.0 dated 2023-08-15

Title: R Interface to 'Keras'
Description: Interface to 'Keras' <https://keras.io>, a high-level neural networks 'API'. 'Keras' was developed with a focus on enabling fast experimentation, supports both convolution based networks and recurrent networks (as well as combinations of the two), and runs seamlessly on both 'CPU' and 'GPU' devices.
Author: Tomasz Kalinowski [ctb, cph, cre], Daniel Falbel [ctb, cph], JJ Allaire [aut, cph], Francois Chollet [aut, cph], RStudio [ctb, cph, fnd], Google [ctb, cph, fnd], Yuan Tang [ctb, cph] , Wouter Van Der Bijl [ctb, cph], Martin Studer [ctb, cph], Sigrid [...truncated...]
Maintainer: Tomasz Kalinowski <tomasz@posit.co>

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More information about keras at CRAN
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Fri, 19 Apr 2024

Package protr updated to version 1.7-1 with previous version 1.7-0 dated 2023-10-30

Title: Generating Various Numerical Representation Schemes for Protein Sequences
Description: Comprehensive toolkit for generating various numerical features of protein sequences described in Xiao et al. (2015) <DOI:10.1093/bioinformatics/btv042>. For full functionality, the software 'ncbi-blast+' is needed, see <https://blast.ncbi.nlm.nih.gov/doc/blast-help/downloadblastdata.html> for more information.
Author: Nan Xiao [aut, cre] , Qing-Song Xu [aut], Dong-Sheng Cao [aut], Sebastian Mueller [ctb]
Maintainer: Nan Xiao <me@nanx.me>

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Package tourr updated to version 1.2.0 with previous version 1.1.0 dated 2023-08-24

Title: Tour Methods for Multivariate Data Visualisation
Description: Implements geodesic interpolation and basis generation functions that allow you to create new tour methods from R.
Author: Hadley Wickham [aut, ctb] , Dianne Cook [aut, cre] , Nick Spyrison [ctb] , Ursula Laa [ctb] , H. Sherry Zhang [ctb] , Stuart Lee [ctb]
Maintainer: Dianne Cook <dicook@monash.edu>

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Package apcluster updated to version 1.4.12 with previous version 1.4.11 dated 2023-09-19

Title: Affinity Propagation Clustering
Description: Implements Affinity Propagation clustering introduced by Frey and Dueck (2007) <DOI:10.1126/science.1136800>. The algorithms are largely analogous to the 'Matlab' code published by Frey and Dueck. The package further provides leveraged affinity propagation and an algorithm for exemplar-based agglomerative clustering that can also be used to join clusters obtained from affinity propagation. Various plotting functions are available for analyzing clustering results.
Author: Ulrich Bodenhofer [aut, cre], Johannes Palme [ctb], Chrats Melkonian [ctb], Andreas Kothmeier [aut], Nikola Kostic [ctb]
Maintainer: Ulrich Bodenhofer <ulrich@bodenhofer.com>

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Package glmnetr updated to version 0.4-5 with previous version 0.4-4 dated 2024-03-23

Title: Nested Cross Validation for the Relaxed Lasso and Other Machine Learning Models
Description: Cross validation informed Relaxed LASSO, Artificial Neural Network (ANN), gradient boosting machine ('xgboost'), Random Forest ('RandomForestSRC'), Recursive Partitioning ('RPART') or step wise regression models are fit. Nested cross validation (or analogous for the random forest) is used to estimate and compare performances between these models with results presented in tabular or graphical means. Calibration plots can also be generated, again based upon (nested) cross validation. For some datasets, for example when the design matrix is not of full rank, 'glmnet' may have very long run times when fitting the relaxed lasso model, from our experience when fitting Cox models on data with many predictors and many patients, making it difficult to get solutions from either glmnet() or cv.glmnet(). This may be remedied with the 'path=TRUE' options when calling glmnet() and cv.glmnet(). Within the glmnetr package the approach of path=TRUE is taken by default. When fitting not a relaxed la [...truncated...]
Author: Walter K Kremers [aut, cre] , Nicholas B Larson [ctb]
Maintainer: Walter K Kremers <kremers.walter@mayo.edu>

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Package aspace updated to version 4.1.2 with previous version 4.1.1 dated 2024-04-17

Title: Functions for Estimating Centrographic Statistics
Description: A collection of functions for computing centrographic statistics (e.g., standard distance, standard deviation ellipse, standard deviation box) for observations taken at point locations. Separate plotting functions have been developed for each measure. Users interested in writing results to ESRI shapefiles can do so by using results from 'aspace' functions as inputs to the convert.to.shapefile() and write.shapefile() functions in the 'shapefiles' library. We intend to provide 'terra' integration for geographic data in a future release. The 'aspace' package was originally conceived to aid in the analysis of spatial patterns of travel behaviour (see Buliung and Remmel 2008 <doi:10.1007/s10109-008-0063-7>).
Author: Tarmo K. Remmel [aut, cre] , Randy Bui [aut], Ron N. Buliung [aut]
Maintainer: Tarmo K. Remmel <remmelt@yorku.ca>

Diff between aspace versions 4.1.1 dated 2024-04-17 and 4.1.2 dated 2024-04-19

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Package PropScrRand updated to version 1.1.2 with previous version 1.1.1 dated 2022-04-23

Title: Propensity Score Methods for Assigning Treatment in Randomized Trials
Description: Contains functions to run propensity-biased allocation to balance covariate distributions in sequential trials and propensity-constrained randomization to balance covariate distributions in trials with known baseline covariates at time of randomization. Currently only supports trials comparing two groups.
Author: Travis Loux
Maintainer: Travis Loux <travis.loux@slu.edu>

Diff between PropScrRand versions 1.1.1 dated 2022-04-23 and 1.1.2 dated 2024-04-19

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Package oHMMed updated to version 1.0.2 with previous version 1.0.1 dated 2023-11-19

Title: HMMs with Ordered Hidden States and Emission Densities
Description: Inference using a class of Hidden Markov models (HMMs) called 'oHMMed'(ordered HMM with emission densities <doi:10.1186/s12859-024-05751-4>): The 'oHMMed' algorithms identify the number of comparably homogeneous regions within observed sequences with autocorrelation patterns. These are modelled as discrete hidden states; the observed data points are then realisations of continuous probability distributions with state-specific means that enable ordering of these distributions. The observed sequence is labelled according to the hidden states, permitting only neighbouring states that are also neighbours within the ordering of their associated distributions. The parameters that characterise these state-specific distributions are then inferred. Relevant for application to genomic sequences, time series, or any other sequence data with serial autocorrelation.
Author: Michal Majka [aut, cre] , Lynette Caitlin Mikula [aut] , Claus Vogl [aut]
Maintainer: Michal Majka <michalmajka@hotmail.com>

Diff between oHMMed versions 1.0.1 dated 2023-11-19 and 1.0.2 dated 2024-04-19

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Package WINS updated to version 1.4.1 with previous version 1.4 dated 2024-04-07

Title: The R WINS Package
Description: Calculate the win statistics (win ratio, net benefit and win odds) for prioritized multiple endpoints, plot the win statistics and win proportions over study time if at least one time-to-event endpoint is analyzed, and simulate datasets with dependent endpoints. The package can handle any type of outcomes (continuous, ordinal, binary, time-to-event) and allow users to perform stratified analysis, inverse probability of censoring weighting (IPCW) and inverse probability of treatment weighting (IPTW) analysis.
Author: Ying Cui [aut, cre], Bo Huang [aut]
Maintainer: Ying Cui <cuiyingbeicheng@gmail.com>

Diff between WINS versions 1.4 dated 2024-04-07 and 1.4.1 dated 2024-04-19

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Package tfruns updated to version 1.5.3 with previous version 1.5.2 dated 2024-01-26

Title: Training Run Tools for 'TensorFlow'
Description: Create and manage unique directories for each 'TensorFlow' training run. Provides a unique, time stamped directory for each run along with functions to retrieve the directory of the latest run or latest several runs.
Author: Tomasz Kalinowski [ctb, cre], Daniel Falbel [ctb], JJ Allaire [aut], RStudio [cph, fnd], Mike Bostock [cph] , Masayuki Tanaka [cph] , jQuery Foundation [cph] , jQuery contributors [cph] , Shaun Bowe [cph] , Materialize [cph] , Yuxi You [cph] , Kevin [...truncated...]
Maintainer: Tomasz Kalinowski <tomasz@rstudio.com>

Diff between tfruns versions 1.5.2 dated 2024-01-26 and 1.5.3 dated 2024-04-19

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Package redcapAPI updated to version 2.9.0 with previous version 2.8.4 dated 2024-01-31

Title: Interface to 'REDCap'
Description: Access data stored in 'REDCap' databases using the Application Programming Interface (API). 'REDCap' (Research Electronic Data CAPture; <https://projectredcap.org>, Harris, et al. (2009) <doi:10.1016/j.jbi.2008.08.010>, Harris, et al. (2019) <doi:10.1016/j.jbi.2019.103208>) is a web application for building and managing online surveys and databases developed at Vanderbilt University. The API allows users to access data and project meta data (such as the data dictionary) from the web programmatically. The 'redcapAPI' package facilitates the process of accessing data with options to prepare an analysis-ready data set consistent with the definitions in a database's data dictionary.
Author: Benjamin Nutter [ctb, aut], Shawn Garbett [cre, ctb] , Savannah Obregon [ctb], Thomas Obadia [ctb], Marcus Lehr [ctb], Brian High [ctb], Stephen Lane [ctb], Will Beasley [ctb], Will Gray [ctb], Nick Kennedy [ctb], Tan Hsi-Nien [ctb], Jeffrey Horner [ [...truncated...]
Maintainer: Shawn Garbett <shawn.garbett@vumc.org>

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 R/deleteArms.R                                                                |   20 
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 R/deleteEvents.R                                                              |   18 
 R/deleteFileRepository.R                                                      |   12 
 R/deleteFromFileRepository.R                                                  |   11 
 R/deleteUserRoles.R                                                           |   12 
 R/deleteUsers.R                                                               |   12 
 R/docsArmsMethods.R                                                           |    5 
 R/docsDagMethods.R                                                            |    3 
 R/docsEventMethods.R                                                          |    3 
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 R/docsFileRepositoryMethods.R                                                 |    3 
 R/docsFromFileRepository.R                                                    |    5 
 R/docsMappingMethods.R                                                        |    3 
 R/docsMetaDataMethods.R                                                       |    5 
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 R/docsUserRoleMethods.R                                                       |    3 
 R/exportFiles.R                                                               |    8 
 R/exportRecordsTyped.R                                                        |    9 
 R/exportReportsTyped.R                                                        |    3 
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 R/reviewInvalidRecords.R                                                      |    2 
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 man/eventsMethods.Rd                                                          |    5 
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 man/mappingMethods.Rd                                                         |    6 
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 man/reviewInvalidRecords.Rd                                                   |    2 
 man/switchDag.Rd                                                              |    4 
 man/unlockREDCap.Rd                                                           |    4 
 man/userMethods.Rd                                                            |    5 
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 man/userRoleMethods.Rd                                                        |    5 
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Package neuralGAM updated to version 1.1.1 with previous version 1.1.0 dated 2023-09-20

Title: Interpretable Neural Network Based on Generalized Additive Models
Description: Neural network framework based on Generalized Additive Models from Hastie & Tibshirani (1990, ISBN:9780412343902), which trains a different neural network to estimate the contribution of each feature to the response variable. The networks are trained independently leveraging the local scoring and backfitting algorithms to ensure that the Generalized Additive Model converges and it is additive. The resultant Neural Network is a highly accurate and interpretable deep learning model, which can be used for high-risk AI practices where decision-making should be based on accountable and interpretable algorithms.
Author: Ines Ortega-Fernandez [aut, cre, cph] , Marta Sestelo [aut, cph]
Maintainer: Ines Ortega-Fernandez <iortega@gradiant.org>

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Package censored updated to version 0.3.1 with previous version 0.3.0 dated 2024-01-31

Title: 'parsnip' Engines for Survival Models
Description: Engines for survival models from the 'parsnip' package. These include parametric models (e.g., Jackson (2016) <doi:10.18637/jss.v070.i08>), semi-parametric (e.g., Simon et al (2011) <doi:10.18637/jss.v039.i05>), and tree-based models (e.g., Buehlmann and Hothorn (2007) <doi:10.1214/07-STS242>).
Author: Emil Hvitfeldt [aut] , Hannah Frick [aut, cre] , Posit Software, PBC [cph, fnd]
Maintainer: Hannah Frick <hannah@posit.co>

Diff between censored versions 0.3.0 dated 2024-01-31 and 0.3.1 dated 2024-04-19

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Package tldr updated to version 0.4.0 with previous version 0.3.0 dated 2023-05-24

Title: T Loux Doing R: Functions to Simplify Data Analysis and Reporting
Description: Gives a number of functions to aid common data analysis processes and reporting statistical results in an 'RMarkdown' file. Data analysis functions combine multiple base R functions used to describe simple bivariate relationships into a single, easy to use function. Reporting functions will return character strings to report p-values, confidence intervals, and hypothesis test and regression results. Strings will be LaTeX-formatted as necessary and will knit pretty in an 'RMarkdown' document. The package also provides wrappers function in the 'tableone' package to make the results knit-able.
Author: Travis Loux [aut, cre]
Maintainer: Travis Loux <travis.loux@slu.edu>

Diff between tldr versions 0.3.0 dated 2023-05-24 and 0.4.0 dated 2024-04-19

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Package cata updated to version 0.1.0.6 with previous version 0.1.0.5 dated 2024-03-04

Title: Analysis of Check-All-that-Apply (CATA) Data
Description: Functions for analyzing check-all-that-apply (CATA) data from consumer and sensory tests. Cochran's Q test, McNemar's test, and Penalty-Lift analysis provided, as described in for CATA data analysis by Meyners, Castura & Carr (2013) <doi:10.1016/j.foodqual.2013.06.010>. Cluster analysis can be performed using b-cluster analysis. The quality of cluster analysis solutions can be evaluated using various measures. The methods related to b-cluster analysis are described in a manuscript by Castura, Meyners, Varela & Næs (2022) <doi:10.1016/j.foodqual.2022.104564>. Methods are adapted to product-related hedonic responses by Castura, Meyners, Pohjanheimo, Varela & Næs (2023) <doi:10.1111/joss.12860>.
Author: J.C. Castura [aut, cre, ctb]
Maintainer: J.C. Castura <jcastura@compusense.com>

Diff between cata versions 0.1.0.5 dated 2024-03-04 and 0.1.0.6 dated 2024-04-19

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Package bundesbank updated to version 0.1-12 with previous version 0.1-11 dated 2023-10-09

Title: Download Data from Bundesbank
Description: Download data from the time-series databases of the Bundesbank, the German central bank. See the overview at the Bundesbank website (<https://www.bundesbank.de/en/statistics/time-series-databases>) for available series. The package provides only a single function, getSeries(), which supports both traditional and real-time datasets; it will also download meta data if available. Downloaded data can automatically be arranged in various formats, such as data frames or 'zoo' series. The data may optionally be cached, so as to avoid repeated downloads of the same series.
Author: Enrico Schumann [aut, cre]
Maintainer: Enrico Schumann <es@enricoschumann.net>

Diff between bundesbank versions 0.1-11 dated 2023-10-09 and 0.1-12 dated 2024-04-19

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Package listarrays updated to version 0.4.0 with previous version 0.3.1 dated 2020-03-08

Title: A Toolbox for Working with R Arrays in a Functional Programming Style
Description: A toolbox for R arrays. Flexibly split, bind, reshape, modify, subset and name arrays.
Author: Tomasz Kalinowski [aut, cre]
Maintainer: Tomasz Kalinowski <kalinowskit@gmail.com>

Diff between listarrays versions 0.3.1 dated 2020-03-08 and 0.4.0 dated 2024-04-19

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Package rib updated to version 0.20.0 with previous version 0.19.3 dated 2023-10-20

Title: An Implementation of 'Interactive Brokers' API
Description: Allows interaction with 'Interactive Brokers' 'Trader Workstation' <https://interactivebrokers.github.io/tws-api/>. Handles the connection over the network and the exchange of messages. Data is encoded and decoded between user and wire formats. Data structures and functionality closely mirror the official implementations.
Author: Luca Billi [aut, cre]
Maintainer: Luca Billi <noreply.section+dev@gmail.com>

Diff between rib versions 0.19.3 dated 2023-10-20 and 0.20.0 dated 2024-04-19

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Package envir updated to version 0.3.0 with previous version 0.2.2 dated 2022-09-22

Title: Manage R Environments Better
Description: Provides a small set of functions for managing R environments, with defaults designed to encourage usage patterns that scale well to larger code bases. It provides: import_from(), a flexible way to assign bindings that defaults to the current environment; include(), a vectorized alternative to base::source() that also default to the current environment; and attach_eval() and attach_source(), a way to evaluate expressions in attached environments. Together, these (and other) functions pair to provide a robust alternative to base::library() and base::source().
Author: Tomasz Kalinowski [aut, cre]
Maintainer: Tomasz Kalinowski <kalinowskit@gmail.com>

Diff between envir versions 0.2.2 dated 2022-09-22 and 0.3.0 dated 2024-04-19

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Package commafree updated to version 0.2.0 with previous version 0.1.0 dated 2022-11-11

Title: Call Functions Without Commas Between Arguments
Description: Provides the "comma-free call" operator: '%(%'. Use it to call a function without commas between the arguments. Just replace the '(' with '%(%' in a function call, supply your arguments as standard R expressions enclosed by '{ }', and be free of commas (for that call).
Author: Tomasz Kalinowski [aut, cre]
Maintainer: Tomasz Kalinowski <kalinowskit@gmail.com>

Diff between commafree versions 0.1.0 dated 2022-11-11 and 0.2.0 dated 2024-04-19

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 4 files changed, 9 insertions(+), 6 deletions(-)

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Package QWDAP updated to version 1.1.18 with previous version 1.1.17 dated 2022-04-01

Title: Quantum Walk-Based Data Analysis and Prediction
Description: The modeling and prediction of graph-associated time series(GATS) based on continuous time quantum walk. This software is mainly used for feature extraction, modeling, prediction and result evaluation of GATS, including continuous time quantum walk simulation, feature selection, regression analysis, time series prediction, and series fit calculation.
Author: Binghuang Pan [aut, cre], Zhaoyuan Yu [aut], Xu Hu [ctb], Yuhao Teng [ctb]
Maintainer: Binghuang Pan <bright1up@163.com>

Diff between QWDAP versions 1.1.17 dated 2022-04-01 and 1.1.18 dated 2024-04-19

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Package linelist updated to version 1.1.2 with previous version 1.1.0 dated 2024-02-28

Title: Tagging and Validating Epidemiological Data
Description: Provides tools to help storing and handling case line list data. The 'linelist' class adds a tagging system to classical 'data.frame' objects to identify key epidemiological data such as dates of symptom onset, epidemiological case definition, age, gender or disease outcome. Once tagged, these variables can be seamlessly used in downstream analyses, making data pipelines more robust and reliable.
Author: Hugo Gruson [aut, cre] , Thibaut Jombart [aut, ccp], Tim Taylor [ctb], Chris Hartgerink [rev]
Maintainer: Hugo Gruson <hugo@data.org>

Diff between linelist versions 1.1.0 dated 2024-02-28 and 1.1.2 dated 2024-04-19

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Package antaresEditObject updated to version 0.6.2 with previous version 0.6.1 dated 2023-12-12

Title: Edit an 'Antares' Simulation
Description: Edit an 'Antares' simulation before running it : create new areas, links, thermal clusters or binding constraints or edit existing ones. Update 'Antares' general & optimization settings. 'Antares' is an open source power system generator, more information available here : <https://antares-simulator.org/>.
Author: Tatiana Vargas [aut, cre], Frederic Breant [aut], Victor Perrier [aut], Baptiste Seguinot [ctb], Benoit Thieurmel [ctb], Titouan Robert [ctb], Jalal-Edine Zawam [ctb], Etienne Sanchez [ctb], Janus De Bondt [ctb], Assil Mansouri [ctb], Abdallah Mahoud [...truncated...]
Maintainer: Tatiana Vargas <tatiana.vargas@rte-france.com>

Diff between antaresEditObject versions 0.6.1 dated 2023-12-12 and 0.6.2 dated 2024-04-19

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Permanent link

Package segmented updated to version 2.0-4 with previous version 2.0-3 dated 2024-02-16

Title: Regression Models with Break-Points / Change-Points Estimation (with Possibly Random Effects)
Description: Fitting regression models where, in addition to possible linear terms, one or more covariates have segmented (i.e., broken-line or piece-wise linear) or stepmented (i.e. piece-wise constant) effects. Multiple breakpoints for the same variable are allowed. The estimation method is discussed in Muggeo (2003, <doi:10.1002/sim.1545>) and illustrated in Muggeo (2008, <https://www.r-project.org/doc/Rnews/Rnews_2008-1.pdf>). An approach for hypothesis testing is presented in Muggeo (2016, <doi:10.1080/00949655.2016.1149855>), and interval estimation for the breakpoint is discussed in Muggeo (2017, <doi:10.1111/anzs.12200>). Segmented mixed models, i.e. random effects in the change point, are discussed in Muggeo (2014, <doi:10.1177/1471082X13504721>). Estimation of piecewise-constant relationships and changepoints (mean-shift models) is discussed in Fasola et al. (2018, <doi:10.1007/s00180-017-0740-4>).
Author: Vito M. R. Muggeo [aut, cre]
Maintainer: Vito M. R. Muggeo <vito.muggeo@unipa.it>

Diff between segmented versions 2.0-3 dated 2024-02-16 and 2.0-4 dated 2024-04-19

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More information about segmented at CRAN
Permanent link

Package espadon updated to version 1.7.0 with previous version 1.6.0 dated 2024-03-07

Title: Easy Study of Patient DICOM Data in Oncology
Description: Exploitation, processing and 2D-3D visualization of DICOM-RT files (structures, dosimetry, imagery) for medical physics and clinical research, in a patient-oriented perspective.
Author: Cathy Fontbonne [aut, cre] , Jean-Marc Fontbonne [aut] , Nathan Azemar [ctb]
Maintainer: Cathy Fontbonne <contact.espadon@lpccaen.in2p3.fr>

Diff between espadon versions 1.6.0 dated 2024-03-07 and 1.7.0 dated 2024-04-19

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More information about espadon at CRAN
Permanent link

Package bioregion updated to version 1.1.1 with previous version 1.1.0 dated 2024-03-19

Title: Comparison of Bioregionalisation Methods
Description: The main purpose of this package is to propose a transparent methodological framework to compare bioregionalisation methods based on hierarchical and non-hierarchical clustering algorithms (Kreft & Jetz (2010) <doi:10.1111/j.1365-2699.2010.02375.x>) and network algorithms (Lenormand et al. (2019) <doi:10.1002/ece3.4718> and Leroy et al. (2019) <doi:10.1111/jbi.13674>).
Author: Maxime Lenormand [aut, cre] , Boris Leroy [aut] , Pierre Denelle [aut]
Maintainer: Maxime Lenormand <maxime.lenormand@inrae.fr>

Diff between bioregion versions 1.1.0 dated 2024-03-19 and 1.1.1 dated 2024-04-19

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More information about bioregion at CRAN
Permanent link

Package NNS updated to version 10.8 with previous version 10.7 dated 2024-03-06

Title: Nonlinear Nonparametric Statistics
Description: Nonlinear nonparametric statistics using partial moments. Partial moments are the elements of variance and asymptotically approximate the area of f(x). These robust statistics provide the basis for nonlinear analysis while retaining linear equivalences. NNS offers: Numerical integration, Numerical differentiation, Clustering, Correlation, Dependence, Causal analysis, ANOVA, Regression, Classification, Seasonality, Autoregressive modeling, Normalization, Stochastic dominance and Advanced Monte Carlo sampling. All routines based on: Viole, F. and Nawrocki, D. (2013), Nonlinear Nonparametric Statistics: Using Partial Moments (ISBN: 1490523995).
Author: Fred Viole [aut, cre], Roberto Spadim [ctb]
Maintainer: Fred Viole <ovvo.financial.systems@gmail.com>

Diff between NNS versions 10.7 dated 2024-03-06 and 10.8 dated 2024-04-19

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Permanent link

Package messydates updated to version 0.4.1 with previous version 0.3.5 dated 2023-01-20

Title: A Flexible Class for Messy Dates
Description: Contains a set of tools for constructing and coercing into and from the "mdate" class. This date class implements ISO 8601-2:2019(E) and allows regular dates to be annotated to express unspecified date components, approximate or uncertain date components, date ranges, and sets of dates. This is useful for describing and analysing temporal information, whether historical or recent, where date precision may vary.
Author: James Hollway [cre, aut, ctb] , Henrique Sposito [ctb] , Jael Tan [ctb] , Nathan Werth [ctb]
Maintainer: James Hollway <james.hollway@graduateinstitute.ch>

Diff between messydates versions 0.3.5 dated 2023-01-20 and 0.4.1 dated 2024-04-19

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Permanent link

Package hdf5r.Extra updated to version 0.0.6 with previous version 0.0.5 dated 2024-01-29

Title: Extensions for 'HDF5' R Interfaces
Description: Some methods to manipulate 'HDF5' files, extending the 'hdf5r' package. Reading and writing R objects to 'HDF5' formats follow the specification of 'AnnData' <https://anndata.readthedocs.io/en/latest/fileformat-prose.html>.
Author: Yuchen Li [aut, cre]
Maintainer: Yuchen Li <ycli1995@outlook.com>

Diff between hdf5r.Extra versions 0.0.5 dated 2024-01-29 and 0.0.6 dated 2024-04-19

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Permanent link

Package fabR updated to version 2.1.0 with previous version 2.0.1 dated 2023-11-02

Title: Wrapper Functions Collection Used in Data Pipelines
Description: The goal of this package is to provide wrapper functions in the data cleaning and cleansing processes. These function helps in messages and interaction with the user, keep track of information in pipelines, help in the wrangling, munging, assessment and visualization of data frame-like material.
Author: Guillaume Fabre [aut, cre], Maelstrom-Research [fnd]
Maintainer: Guillaume Fabre <guijoseph.fabre@gmail.com>

Diff between fabR versions 2.0.1 dated 2023-11-02 and 2.1.0 dated 2024-04-19

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Package BayesMallows updated to version 2.2.0 with previous version 2.1.1 dated 2024-03-15

Title: Bayesian Preference Learning with the Mallows Rank Model
Description: An implementation of the Bayesian version of the Mallows rank model (Vitelli et al., Journal of Machine Learning Research, 2018 <https://jmlr.org/papers/v18/15-481.html>; Crispino et al., Annals of Applied Statistics, 2019 <doi:10.1214/18-AOAS1203>; Sorensen et al., R Journal, 2020 <doi:10.32614/RJ-2020-026>; Stein, PhD Thesis, 2023 <https://eprints.lancs.ac.uk/id/eprint/195759>). Both Metropolis-Hastings and sequential Monte Carlo algorithms for estimating the models are available. Cayley, footrule, Hamming, Kendall, Spearman, and Ulam distances are supported in the models. The rank data to be analyzed can be in the form of complete rankings, top-k rankings, partially missing rankings, as well as consistent and inconsistent pairwise preferences. Several functions for plotting and studying the posterior distributions of parameters are provided. The package also provides functions for estimating the partition function (normalizing constant) of the Mallows rank mo [...truncated...]
Author: Oystein Sorensen [aut, cre] , Waldir Leoncio [aut], Valeria Vitelli [aut] , Marta Crispino [aut], Qinghua Liu [aut], Cristina Mollica [aut], Luca Tardella [aut], Anja Stein [aut]
Maintainer: Oystein Sorensen <oystein.sorensen.1985@gmail.com>

Diff between BayesMallows versions 2.1.1 dated 2024-03-15 and 2.2.0 dated 2024-04-19

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More information about BayesMallows at CRAN
Permanent link

Thu, 18 Apr 2024

Package pkgdown updated to version 2.0.9 with previous version 2.0.8 dated 2024-04-10

Title: Make Static HTML Documentation for a Package
Description: Generate an attractive and useful website from a source package. 'pkgdown' converts your documentation, vignettes, 'README', and more to 'HTML' making it easy to share information about your package online.
Author: Hadley Wickham [aut, cre] , Jay Hesselberth [aut] , Maelle Salmon [aut] , Posit Software, PBC [cph, fnd]
Maintainer: Hadley Wickham <hadley@posit.co>

Diff between pkgdown versions 2.0.8 dated 2024-04-10 and 2.0.9 dated 2024-04-18

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Package fastcpd updated to version 0.14.1 with previous version 0.14.0 dated 2024-04-16

Title: Fast Change Point Detection via Sequential Gradient Descent
Description: Implements fast change point detection algorithm based on the paper "Sequential Gradient Descent and Quasi-Newton's Method for Change-Point Analysis" by Xianyang Zhang, Trisha Dawn <https://proceedings.mlr.press/v206/zhang23b.html>. The algorithm is based on dynamic programming with pruning and sequential gradient descent. It is able to detect change points a magnitude faster than the vanilla Pruned Exact Linear Time(PELT). The package includes examples of linear regression, logistic regression, Poisson regression, penalized linear regression data, and whole lot more examples with custom cost function in case the user wants to use their own cost function.
Author: Xingchi Li [aut, cre, cph] , Xianyang Zhang [aut, cph]
Maintainer: Xingchi Li <anthony.li@stat.tamu.edu>

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Package climetrics updated to version 1.0-15 with previous version 1.0-12 dated 2023-10-04

Title: Climate Change Metrics
Description: A framework that facilitates spatio-temporal analysis of climate dynamics through exploring and measuring different dimensions of climate change in space and time.
Author: Shirin Taheri [cre, aut] , Babak Naimi [aut] , Miguel Araujo [aut]
Maintainer: Shirin Taheri <taheri.shi@gmail.com>

Diff between climetrics versions 1.0-12 dated 2023-10-04 and 1.0-15 dated 2024-04-18

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Package tune updated to version 1.2.1 with previous version 1.2.0 dated 2024-03-20

Title: Tidy Tuning Tools
Description: The ability to tune models is important. 'tune' contains functions and classes to be used in conjunction with other 'tidymodels' packages for finding reasonable values of hyper-parameters in models, pre-processing methods, and post-processing steps.
Author: Max Kuhn [aut, cre] , Posit Software, PBC [cph, fnd]
Maintainer: Max Kuhn <max@posit.co>

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Package pald updated to version 0.0.4 with previous version 0.0.3 dated 2023-09-28

Title: Partitioned Local Depth for Community Structure in Data
Description: Implementation of the Partitioned Local Depth (PaLD) approach which provides a measure of local depth and the cohesion of a point to another which (together with a universal threshold for distinguishing strong and weak ties) may be used to reveal local and global structure in data, based on methods described in Berenhaut, Moore, and Melvin (2022) <doi:10.1073/pnas.2003634119>. No extraneous inputs, distributional assumptions, iterative procedures nor optimization criteria are employed. This package includes functions for computing local depths and cohesion as well as flexible functions for plotting community networks and displays of cohesion against distance.
Author: Katherine Moore [aut] , Kenneth Berenhaut [aut], Lucy D'Agostino McGowan [aut, cre]
Maintainer: Lucy D'Agostino McGowan <lucydagostino@gmail.com>

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Package rqPen updated to version 4.0 with previous version 3.2.2 dated 2024-03-14

Title: Penalized Quantile Regression
Description: Performs penalized quantile regression with LASSO, elastic net, SCAD and MCP penalty functions including group penalties. In addition, offers a group penalty that provides consistent variable selection across quantiles. Provides a function that automatically generates lambdas and evaluates different models with cross validation or BIC, including a large p version of BIC. Below URL provides a link to a work in progress vignette.
Author: Ben Sherwood [aut, cre], Adam Maidman [aut], Shaobo Li [aut]
Maintainer: Ben Sherwood <ben.sherwood@ku.edu>

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Package aqp updated to version 2.0.3 with previous version 2.0.2 dated 2023-11-28

Title: Algorithms for Quantitative Pedology
Description: The Algorithms for Quantitative Pedology (AQP) project was started in 2009 to organize a loosely-related set of concepts and source code on the topic of soil profile visualization, aggregation, and classification into this package (aqp). Over the past 8 years, the project has grown into a suite of related R packages that enhance and simplify the quantitative analysis of soil profile data. Central to the AQP project is a new vocabulary of specialized functions and data structures that can accommodate the inherent complexity of soil profile information; freeing the scientist to focus on ideas rather than boilerplate data processing tasks <doi:10.1016/j.cageo.2012.10.020>. These functions and data structures have been extensively tested and documented, applied to projects involving hundreds of thousands of soil profiles, and deeply integrated into widely used tools such as SoilWeb <https://casoilresource.lawr.ucdavis.edu/soilweb-apps>. Components of the AQP project (aqp, soilD [...truncated...]
Author: Dylan Beaudette [aut, cre], Pierre Roudier [aut, ctb], Andrew Brown [aut, ctb]
Maintainer: Dylan Beaudette <dylan.beaudette@usda.gov>

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Package maq updated to version 0.4.0 with previous version 0.3.1 dated 2023-10-07

Title: Multi-Armed Qini
Description: Evaluate treatment rules for costly and mutually exclusive treatment arms with Qini curves as proposed in Sverdrup, Wu, Athey, and Wager (2023) <doi:10.48550/arXiv.2306.11979>.
Author: Erik Sverdrup [aut, cre], Han Wu [aut], Susan Athey [aut], Stefan Wager [aut]
Maintainer: Erik Sverdrup <erik.sverdrup@monash.edu>

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Package irboost updated to version 0.1-1.5 with previous version 0.1-1.3 dated 2023-06-24

Title: Iteratively Reweighted Boosting for Robust Analysis
Description: Fit a predictive model using iteratively reweighted boosting (IRBoost) to minimize robust loss functions within the CC-family (concave-convex). This constitutes an application of iteratively reweighted convex optimization (IRCO), where convex optimization is performed using the functional descent boosting algorithm. IRBoost assigns weights to facilitate outlier identification. Applications include robust generalized linear models and robust accelerated failure time models. Wang (2021) <doi:10.48550/arXiv.2101.07718>.
Author: Zhu Wang [aut, cre]
Maintainer: Zhu Wang <zhuwang@gmail.com>

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Package glmMisrep updated to version 0.1.1 with previous version 0.1.0 dated 2024-03-26

Title: Generalized Linear Models Adjusting for Misrepresentation
Description: Fit Generalized Linear Models to continuous and count outcomes, as well as estimate the prevalence of misrepresentation of an important binary predictor. Misrepresentation typically arises when there is an incentive for the binary factor to be misclassified in one direction (e.g., in insurance settings where policy holders may purposely deny a risk status in order to lower the insurance premium). This is accomplished by treating a subset of the response variable as resulting from a mixture distribution. Model parameters are estimated via the Expectation Maximization algorithm and standard errors of the estimates are obtained from closed forms of the Observed Fisher Information. For an introduction to the models and the misrepresentation framework, see Xia et. al., (2023) <https://variancejournal.org/article/73151-maximum-likelihood-approaches-to-misrepresentation-models-in-glm-ratemaking-model-comparisons>.
Author: Patrick Rafael [cre, aut], Xia Michelle [aut], Rexford Akakpo [aut]
Maintainer: Patrick Rafael <pbr2608@vt.edu>

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Package geobr updated to version 1.9.0 with previous version 1.8.2 dated 2024-01-09

Title: Download Official Spatial Data Sets of Brazil
Description: Easy access to official spatial data sets of Brazil as 'sf' objects in R. The package includes a wide range of geospatial data available at various geographic scales and for various years with harmonized attributes, projection and fixed topology.
Author: Rafael H. M. Pereira [aut, cre] , Caio Nogueira Goncalves [aut], Paulo Henrique Fernandes de Araujo [ctb], Guilherme Duarte Carvalho [ctb], Rodrigo Almeida de Arruda [ctb], Igor Nascimento [ctb], Barbara Santiago Pedreira da Costa [ctb], Welligtton S [...truncated...]
Maintainer: Rafael H. M. Pereira <rafa.pereira.br@gmail.com>

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More information about geobr at CRAN
Permanent link

Package VancouvR updated to version 0.1.8 with previous version 0.1.7 dated 2021-10-21

Title: Access the 'City of Vancouver' Open Data API
Description: Wrapper around the 'City of Vancouver' Open Data API <https://opendata.vancouver.ca/api/v2/console> to simplify and standardize access to 'City of Vancouver' open data. Functionality to list the data catalogue and access data and geographic records.
Author: Jens von Bergmann
Maintainer: Jens von Bergmann <jens@mountainmath.ca>

Diff between VancouvR versions 0.1.7 dated 2021-10-21 and 0.1.8 dated 2024-04-18

 DESCRIPTION            |   11 -
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 vignettes/Isolines.Rmd |    2 
 15 files changed, 729 insertions(+), 263 deletions(-)

More information about VancouvR at CRAN
Permanent link

Package rjsoncons updated to version 1.3.0 with previous version 1.2.0 dated 2024-01-26

Title: Query, Pivot, Patch, and Validate 'JSON' and 'NDJSON'
Description: Functions to query (filter or transform), pivot (convert from array-of-objects to object-of-arrays, for easy import as 'R' data frame), search, patch (edit), and validate (against 'JSON Schema') 'JSON' and 'NDJSON' strings, files, or URLs. Query and pivot support 'JSONpointer', 'JSONpath' or 'JMESpath' expressions. The implementation uses the 'jsoncons' <https://danielaparker.github.io/jsoncons/> header-only library; the library is easily linked to other packages for direct access to 'C++' functionality not implemented here.
Author: Martin Morgan [aut, cre] , Marcel Ramos [aut] , Daniel Parker [aut, cph]
Maintainer: Martin Morgan <mtmorgan.xyz@gmail.com>

Diff between rjsoncons versions 1.2.0 dated 2024-01-26 and 1.3.0 dated 2024-04-18

 rjsoncons-1.2.0/rjsoncons/R/j_query.R                                                         |only
 rjsoncons-1.2.0/rjsoncons/R/json.R                                                            |only
 rjsoncons-1.2.0/rjsoncons/R/ndjson.R                                                          |only
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 rjsoncons-1.2.0/rjsoncons/src/utilities.h                                                     |only
 rjsoncons-1.3.0/rjsoncons/DESCRIPTION                                                         |   35 
 rjsoncons-1.3.0/rjsoncons/MD5                                                                 |  370 ++---
 rjsoncons-1.3.0/rjsoncons/NAMESPACE                                                           |   17 
 rjsoncons-1.3.0/rjsoncons/NEWS.md                                                             |   60 
 rjsoncons-1.3.0/rjsoncons/R/as_r.R                                                            |   41 
 rjsoncons-1.3.0/rjsoncons/R/cpp11.R                                                           |   52 
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 rjsoncons-1.3.0/rjsoncons/R/flatten.R                                                         |only
 rjsoncons-1.3.0/rjsoncons/R/j_data_type.R                                                     |    6 
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 rjsoncons-1.3.0/rjsoncons/R/paths_and_pointer.R                                               |   12 
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 rjsoncons-1.3.0/rjsoncons/R/schema.R                                                          |only
 rjsoncons-1.3.0/rjsoncons/R/utilities.R                                                       |   24 
 rjsoncons-1.3.0/rjsoncons/R/version.R                                                         |    7 
 rjsoncons-1.3.0/rjsoncons/README.md                                                           |   30 
 rjsoncons-1.3.0/rjsoncons/build/vignette.rds                                                  |binary
 rjsoncons-1.3.0/rjsoncons/inst/doc/a_rjsoncons.R                                              |  137 +
 rjsoncons-1.3.0/rjsoncons/inst/doc/a_rjsoncons.Rmd                                            |  349 ++++
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 rjsoncons-1.3.0/rjsoncons/inst/include/jsoncons/allocator_set.hpp                             |    2 
 rjsoncons-1.3.0/rjsoncons/inst/include/jsoncons/basic_json.hpp                                |  146 +-
 rjsoncons-1.3.0/rjsoncons/inst/include/jsoncons/byte_string.hpp                               |    2 
 rjsoncons-1.3.0/rjsoncons/inst/include/jsoncons/config/compiler_support.hpp                   |   26 
 rjsoncons-1.3.0/rjsoncons/inst/include/jsoncons/config/jsoncons_config.hpp                    |   13 
 rjsoncons-1.3.0/rjsoncons/inst/include/jsoncons/config/version.hpp                            |    4 
 rjsoncons-1.3.0/rjsoncons/inst/include/jsoncons/conv_error.hpp                                |    2 
 rjsoncons-1.3.0/rjsoncons/inst/include/jsoncons/decode_json.hpp                               |    2 
 rjsoncons-1.3.0/rjsoncons/inst/include/jsoncons/decode_traits.hpp                             |    2 
 rjsoncons-1.3.0/rjsoncons/inst/include/jsoncons/detail/endian.hpp                             |    2 
 rjsoncons-1.3.0/rjsoncons/inst/include/jsoncons/detail/heap_string.hpp                        |    2 
 rjsoncons-1.3.0/rjsoncons/inst/include/jsoncons/detail/optional.hpp                           |    2 
 rjsoncons-1.3.0/rjsoncons/inst/include/jsoncons/detail/parse_number.hpp                       |   47 
 rjsoncons-1.3.0/rjsoncons/inst/include/jsoncons/detail/string_view.hpp                        |    2 
 rjsoncons-1.3.0/rjsoncons/inst/include/jsoncons/detail/write_number.hpp                       |    2 
 rjsoncons-1.3.0/rjsoncons/inst/include/jsoncons/encode_json.hpp                               |    2 
 rjsoncons-1.3.0/rjsoncons/inst/include/jsoncons/encode_traits.hpp                             |    2 
 rjsoncons-1.3.0/rjsoncons/inst/include/jsoncons/extension_traits.hpp                          |    2 
 rjsoncons-1.3.0/rjsoncons/inst/include/jsoncons/item_event_visitor.hpp                        |    2 
 rjsoncons-1.3.0/rjsoncons/inst/include/jsoncons/json.hpp                                      |    2 
 rjsoncons-1.3.0/rjsoncons/inst/include/jsoncons/json_array.hpp                                |    2 
 rjsoncons-1.3.0/rjsoncons/inst/include/jsoncons/json_content_handler.hpp                      |    2 
 rjsoncons-1.3.0/rjsoncons/inst/include/jsoncons/json_cursor.hpp                               |   19 
 rjsoncons-1.3.0/rjsoncons/inst/include/jsoncons/json_decoder.hpp                              |    2 
 rjsoncons-1.3.0/rjsoncons/inst/include/jsoncons/json_encoder.hpp                              |  139 +
 rjsoncons-1.3.0/rjsoncons/inst/include/jsoncons/json_error.hpp                                |    2 
 rjsoncons-1.3.0/rjsoncons/inst/include/jsoncons/json_exception.hpp                            |    2 
 rjsoncons-1.3.0/rjsoncons/inst/include/jsoncons/json_filter.hpp                               |    9 
 rjsoncons-1.3.0/rjsoncons/inst/include/jsoncons/json_fwd.hpp                                  |    2 
 rjsoncons-1.3.0/rjsoncons/inst/include/jsoncons/json_object.hpp                               |   79 -
 rjsoncons-1.3.0/rjsoncons/inst/include/jsoncons/json_options.hpp                              |   31 
 rjsoncons-1.3.0/rjsoncons/inst/include/jsoncons/json_parser.hpp                               |    2 
 rjsoncons-1.3.0/rjsoncons/inst/include/jsoncons/json_reader.hpp                               |   11 
 rjsoncons-1.3.0/rjsoncons/inst/include/jsoncons/json_traits_macros.hpp                        |    2 
 rjsoncons-1.3.0/rjsoncons/inst/include/jsoncons/json_traits_macros_deprecated.hpp             |    2 
 rjsoncons-1.3.0/rjsoncons/inst/include/jsoncons/json_type.hpp                                 |    2 
 rjsoncons-1.3.0/rjsoncons/inst/include/jsoncons/json_type_traits.hpp                          |    2 
 rjsoncons-1.3.0/rjsoncons/inst/include/jsoncons/json_visitor.hpp                              |    6 
 rjsoncons-1.3.0/rjsoncons/inst/include/jsoncons/pretty_print.hpp                              |    2 
 rjsoncons-1.3.0/rjsoncons/inst/include/jsoncons/ser_context.hpp                               |    2 
 rjsoncons-1.3.0/rjsoncons/inst/include/jsoncons/sink.hpp                                      |    2 
 rjsoncons-1.3.0/rjsoncons/inst/include/jsoncons/source.hpp                                    |    6 
 rjsoncons-1.3.0/rjsoncons/inst/include/jsoncons/source_adaptor.hpp                            |    2 
 rjsoncons-1.3.0/rjsoncons/inst/include/jsoncons/staj_cursor.hpp                               |  492 ------
 rjsoncons-1.3.0/rjsoncons/inst/include/jsoncons/staj_event.hpp                                |only
 rjsoncons-1.3.0/rjsoncons/inst/include/jsoncons/staj_event_reader.hpp                         |only
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 rjsoncons-1.3.0/rjsoncons/inst/include/jsoncons/tag_type.hpp                                  |    2 
 rjsoncons-1.3.0/rjsoncons/inst/include/jsoncons/text_source_adaptor.hpp                       |    2 
 rjsoncons-1.3.0/rjsoncons/inst/include/jsoncons/typed_array_view.hpp                          |    2 
 rjsoncons-1.3.0/rjsoncons/inst/include/jsoncons/unicode_traits.hpp                            |    2 
 rjsoncons-1.3.0/rjsoncons/inst/include/jsoncons/uri.hpp                                       |  723 ++++++++--
 rjsoncons-1.3.0/rjsoncons/inst/include/jsoncons/value_converter.hpp                           |    2 
 rjsoncons-1.3.0/rjsoncons/inst/include/jsoncons_ext/bson/bson.hpp                             |    2 
 rjsoncons-1.3.0/rjsoncons/inst/include/jsoncons_ext/bson/bson_cursor.hpp                      |    4 
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 rjsoncons-1.3.0/rjsoncons/inst/include/jsoncons_ext/bson/encode_bson.hpp                      |    2 
 rjsoncons-1.3.0/rjsoncons/inst/include/jsoncons_ext/cbor/cbor.hpp                             |    2 
 rjsoncons-1.3.0/rjsoncons/inst/include/jsoncons_ext/cbor/cbor_cursor.hpp                      |    2 
 rjsoncons-1.3.0/rjsoncons/inst/include/jsoncons_ext/cbor/cbor_detail.hpp                      |    2 
 rjsoncons-1.3.0/rjsoncons/inst/include/jsoncons_ext/cbor/cbor_encoder.hpp                     |   10 
 rjsoncons-1.3.0/rjsoncons/inst/include/jsoncons_ext/cbor/cbor_error.hpp                       |    3 
 rjsoncons-1.3.0/rjsoncons/inst/include/jsoncons_ext/cbor/cbor_event_reader.hpp                |    8 
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 rjsoncons-1.3.0/rjsoncons/inst/include/jsoncons_ext/cbor/cbor_parser.hpp                      |    2 
 rjsoncons-1.3.0/rjsoncons/inst/include/jsoncons_ext/cbor/cbor_reader.hpp                      |    2 
 rjsoncons-1.3.0/rjsoncons/inst/include/jsoncons_ext/cbor/decode_cbor.hpp                      |    2 
 rjsoncons-1.3.0/rjsoncons/inst/include/jsoncons_ext/cbor/encode_cbor.hpp                      |    2 
 rjsoncons-1.3.0/rjsoncons/inst/include/jsoncons_ext/csv/csv.hpp                               |    2 
 rjsoncons-1.3.0/rjsoncons/inst/include/jsoncons_ext/csv/csv_cursor.hpp                        |   10 
 rjsoncons-1.3.0/rjsoncons/inst/include/jsoncons_ext/csv/csv_encoder.hpp                       |    2 
 rjsoncons-1.3.0/rjsoncons/inst/include/jsoncons_ext/csv/csv_error.hpp                         |    2 
 rjsoncons-1.3.0/rjsoncons/inst/include/jsoncons_ext/csv/csv_options.hpp                       |    6 
 rjsoncons-1.3.0/rjsoncons/inst/include/jsoncons_ext/csv/csv_parser.hpp                        |    2 
 rjsoncons-1.3.0/rjsoncons/inst/include/jsoncons_ext/csv/csv_reader.hpp                        |   12 
 rjsoncons-1.3.0/rjsoncons/inst/include/jsoncons_ext/csv/csv_serializer.hpp                    |    2 
 rjsoncons-1.3.0/rjsoncons/inst/include/jsoncons_ext/csv/decode_csv.hpp                        |    2 
 rjsoncons-1.3.0/rjsoncons/inst/include/jsoncons_ext/csv/encode_csv.hpp                        |    2 
 rjsoncons-1.3.0/rjsoncons/inst/include/jsoncons_ext/jmespath/jmespath.hpp                     |    4 
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 rjsoncons-1.3.0/rjsoncons/inst/include/jsoncons_ext/jsonpatch/jsonpatch.hpp                   |   10 
 rjsoncons-1.3.0/rjsoncons/inst/include/jsoncons_ext/jsonpatch/jsonpatch_error.hpp             |    2 
 rjsoncons-1.3.0/rjsoncons/inst/include/jsoncons_ext/jsonpath/expression.hpp                   |    7 
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 rjsoncons-1.3.0/rjsoncons/inst/include/jsoncons_ext/jsonpath/path_node.hpp                    |    2 
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Package graphicalExtremes updated to version 0.3.2 with previous version 0.3.1 dated 2024-02-22

Title: Statistical Methodology for Graphical Extreme Value Models
Description: Statistical methodology for sparse multivariate extreme value models. Methods are provided for exact simulation and statistical inference for multivariate Pareto distributions on graphical structures as described in the paper 'Graphical Models for Extremes' by Engelke and Hitz (2020) <doi:10.1111/rssb.12355>.
Author: Sebastian Engelke [aut, cre], Adrien S. Hitz [aut], Nicola Gnecco [aut], Manuel Hentschel [aut]
Maintainer: Sebastian Engelke <sebastian.engelke@unige.ch>

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Package rnndescent updated to version 0.1.5 with previous version 0.1.4 dated 2024-03-18

Title: Nearest Neighbor Descent Method for Approximate Nearest Neighbors
Description: The Nearest Neighbor Descent method for finding approximate nearest neighbors by Dong and co-workers (2010) <doi:10.1145/1963405.1963487>. Based on the 'Python' package 'PyNNDescent' <https://github.com/lmcinnes/pynndescent>.
Author: James Melville [aut, cre, cph], Vitalie Spinu [ctb], Ralf Stubner [ctb]
Maintainer: James Melville <jlmelville@gmail.com>

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Package felp updated to version 0.5.0 with previous version 0.4.0 dated 2024-03-29

Title: Functional Help for Functions, Objects, and Packages
Description: Enhance R help system by fuzzy search and preview interface, pseudo-postfix operators, and more. The `?.` pseudo-postfix operator and the `?` prefix operator displays documents and contents (source or structure) of objects simultaneously to help understanding the objects. The `?p` pseudo-postfix operator displays package documents, and is shorter than help(package = foo).
Author: Atsushi Yasumoto [aut, cph, cre]
Maintainer: Atsushi Yasumoto <atusy.rpkg@gmail.com>

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Package batchmix updated to version 2.2.0 with previous version 2.1.0 dated 2024-02-24

Title: Semi-Supervised Bayesian Mixture Models Incorporating Batch Correction
Description: Semi-supervised and unsupervised Bayesian mixture models that simultaneously infer the cluster/class structure and a batch correction. Densities available are the multivariate normal and the multivariate t. The model sampler is implemented in C++. This package is aimed at analysis of low-dimensional data generated across several batches. See Coleman et al. (2022) <doi:10.1101/2022.01.14.476352> for details of the model.
Author: Stephen Coleman [aut, cre], Paul Kirk [aut], Chris Wallace [aut]
Maintainer: Stephen Coleman <stcolema@tcd.ie>

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Package multbxxc updated to version 1.0.2 with previous version 1.0.1 dated 2019-11-15

Title: Auxiliary Routines for Influx Software
Description: Contains auxiliary routines for influx software. This packages is not intended to be used directly. Influx was published here: Sokol et al. (2012) <doi:10.1093/bioinformatics/btr716>.
Author: Serguei Sokol
Maintainer: Serguei Sokol <sokol@insa-toulouse.fr>

Diff between multbxxc versions 1.0.1 dated 2019-11-15 and 1.0.2 dated 2024-04-18

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Package keras3 updated to version 0.2.0 with previous version 0.1.0 dated 2024-02-17

Title: R Interface to 'Keras'
Description: Interface to 'Keras' <https://keras.io>, a high-level neural networks API. 'Keras' was developed with a focus on enabling fast experimentation, supports both convolution based networks and recurrent networks (as well as combinations of the two), and runs seamlessly on both CPU and GPU devices.
Author: Tomasz Kalinowski [aut, cph, cre], Daniel Falbel [ctb, cph], JJ Allaire [aut, cph], Francois Chollet [aut, cph], Posit Software, PBC [cph, fnd], Google [cph, fnd], Yuan Tang [ctb, cph] , Wouter Van Der Bijl [ctb, cph], Martin Studer [ctb, cph], Sigri [...truncated...]
Maintainer: Tomasz Kalinowski <tomasz@posit.co>

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 keras3-0.2.0/keras3/man/layer_add.Rd                                           |    3 
 keras3-0.2.0/keras3/man/layer_additive_attention.Rd                            |    3 
 keras3-0.2.0/keras3/man/layer_alpha_dropout.Rd                                 |    3 
 keras3-0.2.0/keras3/man/layer_attention.Rd                                     |    3 
 keras3-0.2.0/keras3/man/layer_average.Rd                                       |    3 
 keras3-0.2.0/keras3/man/layer_average_pooling_1d.Rd                            |    3 
 keras3-0.2.0/keras3/man/layer_average_pooling_2d.Rd                            |    5 
 keras3-0.2.0/keras3/man/layer_average_pooling_3d.Rd                            |    5 
 keras3-0.2.0/keras3/man/layer_batch_normalization.Rd                           |    3 
 keras3-0.2.0/keras3/man/layer_bidirectional.Rd                                 |    3 
 keras3-0.2.0/keras3/man/layer_category_encoding.Rd                             |    8 
 keras3-0.2.0/keras3/man/layer_center_crop.Rd                                   |    4 
 keras3-0.2.0/keras3/man/layer_concatenate.Rd                                   |    3 
 keras3-0.2.0/keras3/man/layer_conv_1d.Rd                                       |    5 
 keras3-0.2.0/keras3/man/layer_conv_1d_transpose.Rd                             |    5 
 keras3-0.2.0/keras3/man/layer_conv_2d.Rd                                       |    5 
 keras3-0.2.0/keras3/man/layer_conv_2d_transpose.Rd                             |    5 
 keras3-0.2.0/keras3/man/layer_conv_3d.Rd                                       |    5 
 keras3-0.2.0/keras3/man/layer_conv_3d_transpose.Rd                             |    5 
 keras3-0.2.0/keras3/man/layer_conv_lstm_1d.Rd                                  |    3 
 keras3-0.2.0/keras3/man/layer_conv_lstm_2d.Rd                                  |    3 
 keras3-0.2.0/keras3/man/layer_conv_lstm_3d.Rd                                  |    3 
 keras3-0.2.0/keras3/man/layer_cropping_1d.Rd                                   |    5 
 keras3-0.2.0/keras3/man/layer_cropping_2d.Rd                                   |    5 
 keras3-0.2.0/keras3/man/layer_cropping_3d.Rd                                   |    5 
 keras3-0.2.0/keras3/man/layer_dense.Rd                                         |    3 
 keras3-0.2.0/keras3/man/layer_depthwise_conv_1d.Rd                             |    5 
 keras3-0.2.0/keras3/man/layer_depthwise_conv_2d.Rd                             |    5 
 keras3-0.2.0/keras3/man/layer_discretization.Rd                                |    4 
 keras3-0.2.0/keras3/man/layer_dot.Rd                                           |    3 
 keras3-0.2.0/keras3/man/layer_dropout.Rd                                       |    3 
 keras3-0.2.0/keras3/man/layer_einsum_dense.Rd                                  |    7 
 keras3-0.2.0/keras3/man/layer_embedding.Rd                                     |   17 
 keras3-0.2.0/keras3/man/layer_feature_space.Rd                                 |    5 
 keras3-0.2.0/keras3/man/layer_flatten.Rd                                       |    5 
 keras3-0.2.0/keras3/man/layer_flax_module_wrapper.Rd                           |only
 keras3-0.2.0/keras3/man/layer_gaussian_dropout.Rd                              |    3 
 keras3-0.2.0/keras3/man/layer_gaussian_noise.Rd                                |    3 
 keras3-0.2.0/keras3/man/layer_global_average_pooling_1d.Rd                     |    3 
 keras3-0.2.0/keras3/man/layer_global_average_pooling_2d.Rd                     |    3 
 keras3-0.2.0/keras3/man/layer_global_average_pooling_3d.Rd                     |    3 
 keras3-0.2.0/keras3/man/layer_global_max_pooling_1d.Rd                         |    3 
 keras3-0.2.0/keras3/man/layer_global_max_pooling_2d.Rd                         |    3 
 keras3-0.2.0/keras3/man/layer_global_max_pooling_3d.Rd                         |    3 
 keras3-0.2.0/keras3/man/layer_group_normalization.Rd                           |    3 
 keras3-0.2.0/keras3/man/layer_group_query_attention.Rd                         |    3 
 keras3-0.2.0/keras3/man/layer_gru.Rd                                           |    8 
 keras3-0.2.0/keras3/man/layer_hashed_crossing.Rd                               |    4 
 keras3-0.2.0/keras3/man/layer_hashing.Rd                                       |    4 
 keras3-0.2.0/keras3/man/layer_identity.Rd                                      |    3 
 keras3-0.2.0/keras3/man/layer_integer_lookup.Rd                                |    6 
 keras3-0.2.0/keras3/man/layer_jax_model_wrapper.Rd                             |only
 keras3-0.2.0/keras3/man/layer_lambda.Rd                                        |    3 
 keras3-0.2.0/keras3/man/layer_layer_normalization.Rd                           |    3 
 keras3-0.2.0/keras3/man/layer_lstm.Rd                                          |    8 
 keras3-0.2.0/keras3/man/layer_masking.Rd                                       |    3 
 keras3-0.2.0/keras3/man/layer_max_pooling_1d.Rd                                |    3 
 keras3-0.2.0/keras3/man/layer_max_pooling_2d.Rd                                |    3 
 keras3-0.2.0/keras3/man/layer_max_pooling_3d.Rd                                |    3 
 keras3-0.2.0/keras3/man/layer_maximum.Rd                                       |    3 
 keras3-0.2.0/keras3/man/layer_mel_spectrogram.Rd                               |only
 keras3-0.2.0/keras3/man/layer_minimum.Rd                                       |    3 
 keras3-0.2.0/keras3/man/layer_multi_head_attention.Rd                          |    3 
 keras3-0.2.0/keras3/man/layer_multiply.Rd                                      |    3 
 keras3-0.2.0/keras3/man/layer_normalization.Rd                                 |    4 
 keras3-0.2.0/keras3/man/layer_permute.Rd                                       |    5 
 keras3-0.2.0/keras3/man/layer_random_brightness.Rd                             |    8 
 keras3-0.2.0/keras3/man/layer_random_contrast.Rd                               |    4 
 keras3-0.2.0/keras3/man/layer_random_crop.Rd                                   |    4 
 keras3-0.2.0/keras3/man/layer_random_flip.Rd                                   |    4 
 keras3-0.2.0/keras3/man/layer_random_rotation.Rd                               |    6 
 keras3-0.2.0/keras3/man/layer_random_translation.Rd                            |    4 
 keras3-0.2.0/keras3/man/layer_random_zoom.Rd                                   |    4 
 keras3-0.2.0/keras3/man/layer_repeat_vector.Rd                                 |    5 
 keras3-0.2.0/keras3/man/layer_rescaling.Rd                                     |    4 
 keras3-0.2.0/keras3/man/layer_reshape.Rd                                       |    3 
 keras3-0.2.0/keras3/man/layer_resizing.Rd                                      |    4 
 keras3-0.2.0/keras3/man/layer_rnn.Rd                                           |    3 
 keras3-0.2.0/keras3/man/layer_separable_conv_1d.Rd                             |    5 
 keras3-0.2.0/keras3/man/layer_separable_conv_2d.Rd                             |    5 
 keras3-0.2.0/keras3/man/layer_simple_rnn.Rd                                    |    3 
 keras3-0.2.0/keras3/man/layer_spatial_dropout_1d.Rd                            |    3 
 keras3-0.2.0/keras3/man/layer_spatial_dropout_2d.Rd                            |    3 
 keras3-0.2.0/keras3/man/layer_spatial_dropout_3d.Rd                            |    3 
 keras3-0.2.0/keras3/man/layer_spectral_normalization.Rd                        |    3 
 keras3-0.2.0/keras3/man/layer_string_lookup.Rd                                 |    6 
 keras3-0.2.0/keras3/man/layer_subtract.Rd                                      |    3 
 keras3-0.2.0/keras3/man/layer_text_vectorization.Rd                            |    6 
 keras3-0.2.0/keras3/man/layer_tfsm.Rd                                          |    7 
 keras3-0.2.0/keras3/man/layer_time_distributed.Rd                              |    3 
 keras3-0.2.0/keras3/man/layer_torch_module_wrapper.Rd                          |   40 
 keras3-0.2.0/keras3/man/layer_unit_normalization.Rd                            |    5 
 keras3-0.2.0/keras3/man/layer_upsampling_1d.Rd                                 |   10 
 keras3-0.2.0/keras3/man/layer_upsampling_2d.Rd                                 |    5 
 keras3-0.2.0/keras3/man/layer_upsampling_3d.Rd                                 |    5 
 keras3-0.2.0/keras3/man/layer_zero_padding_1d.Rd                               |    5 
 keras3-0.2.0/keras3/man/layer_zero_padding_2d.Rd                               |    5 
 keras3-0.2.0/keras3/man/layer_zero_padding_3d.Rd                               |    5 
 keras3-0.2.0/keras3/man/learning_rate_schedule_cosine_decay_restarts.Rd        |    6 
 keras3-0.2.0/keras3/man/loss_binary_crossentropy.Rd                            |    1 
 keras3-0.2.0/keras3/man/loss_binary_focal_crossentropy.Rd                      |    1 
 keras3-0.2.0/keras3/man/loss_categorical_crossentropy.Rd                       |    1 
 keras3-0.2.0/keras3/man/loss_categorical_focal_crossentropy.Rd                 |    1 
 keras3-0.2.0/keras3/man/loss_categorical_hinge.Rd                              |    1 
 keras3-0.2.0/keras3/man/loss_cosine_similarity.Rd                              |    1 
 keras3-0.2.0/keras3/man/loss_dice.Rd                                           |only
 keras3-0.2.0/keras3/man/loss_hinge.Rd                                          |    1 
 keras3-0.2.0/keras3/man/loss_huber.Rd                                          |    1 
 keras3-0.2.0/keras3/man/loss_kl_divergence.Rd                                  |    1 
 keras3-0.2.0/keras3/man/loss_log_cosh.Rd                                       |    1 
 keras3-0.2.0/keras3/man/loss_mean_absolute_error.Rd                            |    1 
 keras3-0.2.0/keras3/man/loss_mean_absolute_percentage_error.Rd                 |    1 
 keras3-0.2.0/keras3/man/loss_mean_squared_error.Rd                             |    1 
 keras3-0.2.0/keras3/man/loss_mean_squared_logarithmic_error.Rd                 |    1 
 keras3-0.2.0/keras3/man/loss_poisson.Rd                                        |    1 
 keras3-0.2.0/keras3/man/loss_sparse_categorical_crossentropy.Rd                |    1 
 keras3-0.2.0/keras3/man/loss_squared_hinge.Rd                                  |    1 
 keras3-0.2.0/keras3/man/metric_auc.Rd                                          |    2 
 keras3-0.2.0/keras3/man/metric_binary_crossentropy.Rd                          |    1 
 keras3-0.2.0/keras3/man/metric_binary_focal_crossentropy.Rd                    |    1 
 keras3-0.2.0/keras3/man/metric_categorical_crossentropy.Rd                     |    1 
 keras3-0.2.0/keras3/man/metric_categorical_focal_crossentropy.Rd               |    1 
 keras3-0.2.0/keras3/man/metric_categorical_hinge.Rd                            |    1 
 keras3-0.2.0/keras3/man/metric_hinge.Rd                                        |    1 
 keras3-0.2.0/keras3/man/metric_huber.Rd                                        |    1 
 keras3-0.2.0/keras3/man/metric_kl_divergence.Rd                                |    1 
 keras3-0.2.0/keras3/man/metric_log_cosh.Rd                                     |    1 
 keras3-0.2.0/keras3/man/metric_mean_absolute_error.Rd                          |    1 
 keras3-0.2.0/keras3/man/metric_mean_absolute_percentage_error.Rd               |    1 
 keras3-0.2.0/keras3/man/metric_mean_squared_error.Rd                           |    1 
 keras3-0.2.0/keras3/man/metric_mean_squared_logarithmic_error.Rd               |    1 
 keras3-0.2.0/keras3/man/metric_mean_wrapper.Rd                                 |    2 
 keras3-0.2.0/keras3/man/metric_poisson.Rd                                      |    1 
 keras3-0.2.0/keras3/man/metric_recall.Rd                                       |    2 
 keras3-0.2.0/keras3/man/metric_recall_at_precision.Rd                          |    2 
 keras3-0.2.0/keras3/man/metric_sparse_categorical_crossentropy.Rd              |    1 
 keras3-0.2.0/keras3/man/metric_squared_hinge.Rd                                |    1 
 keras3-0.2.0/keras3/man/normalize.Rd                                           |    1 
 keras3-0.2.0/keras3/man/op_abs.Rd                                              |   17 
 keras3-0.2.0/keras3/man/op_add.Rd                                              |   34 
 keras3-0.2.0/keras3/man/op_all.Rd                                              |   17 
 keras3-0.2.0/keras3/man/op_any.Rd                                              |   20 
 keras3-0.2.0/keras3/man/op_append.Rd                                           |   17 
 keras3-0.2.0/keras3/man/op_arange.Rd                                           |   21 
 keras3-0.2.0/keras3/man/op_arccos.Rd                                           |   17 
 keras3-0.2.0/keras3/man/op_arccosh.Rd                                          |   17 
 keras3-0.2.0/keras3/man/op_arcsin.Rd                                           |   17 
 keras3-0.2.0/keras3/man/op_arcsinh.Rd                                          |   17 
 keras3-0.2.0/keras3/man/op_arctan.Rd                                           |   17 
 keras3-0.2.0/keras3/man/op_arctan2.Rd                                          |   17 
 keras3-0.2.0/keras3/man/op_arctanh.Rd                                          |   17 
 keras3-0.2.0/keras3/man/op_argmax.Rd                                           |   21 
 keras3-0.2.0/keras3/man/op_argmin.Rd                                           |   21 
 keras3-0.2.0/keras3/man/op_argsort.Rd                                          |   17 
 keras3-0.2.0/keras3/man/op_array.Rd                                            |   24 
 keras3-0.2.0/keras3/man/op_average.Rd                                          |   17 
 keras3-0.2.0/keras3/man/op_average_pool.Rd                                     |   17 
 keras3-0.2.0/keras3/man/op_batch_normalization.Rd                              |only
 keras3-0.2.0/keras3/man/op_binary_crossentropy.Rd                              |   17 
 keras3-0.2.0/keras3/man/op_bincount.Rd                                         |   22 
 keras3-0.2.0/keras3/man/op_broadcast_to.Rd                                     |   17 
 keras3-0.2.0/keras3/man/op_cast.Rd                                             |   16 
 keras3-0.2.0/keras3/man/op_categorical_crossentropy.Rd                         |   17 
 keras3-0.2.0/keras3/man/op_ceil.Rd                                             |   17 
 keras3-0.2.0/keras3/man/op_cholesky.Rd                                         |only
 keras3-0.2.0/keras3/man/op_clip.Rd                                             |   17 
 keras3-0.2.0/keras3/man/op_concatenate.Rd                                      |   17 
 keras3-0.2.0/keras3/man/op_cond.Rd                                             |   16 
 keras3-0.2.0/keras3/man/op_conj.Rd                                             |   17 
 keras3-0.2.0/keras3/man/op_conv.Rd                                             |   17 
 keras3-0.2.0/keras3/man/op_conv_transpose.Rd                                   |   17 
 keras3-0.2.0/keras3/man/op_convert_to_numpy.Rd                                 |   16 
 keras3-0.2.0/keras3/man/op_convert_to_tensor.Rd                                |   23 
 keras3-0.2.0/keras3/man/op_copy.Rd                                             |   17 
 keras3-0.2.0/keras3/man/op_correlate.Rd                                        |only
 keras3-0.2.0/keras3/man/op_cos.Rd                                              |   17 
 keras3-0.2.0/keras3/man/op_cosh.Rd                                             |   17 
 keras3-0.2.0/keras3/man/op_count_nonzero.Rd                                    |   17 
 keras3-0.2.0/keras3/man/op_cross.Rd                                            |   17 
 keras3-0.2.0/keras3/man/op_ctc_loss.Rd                                         |   17 
 keras3-0.2.0/keras3/man/op_cumprod.Rd                                          |   17 
 keras3-0.2.0/keras3/man/op_cumsum.Rd                                           |   17 
 keras3-0.2.0/keras3/man/op_custom_gradient.Rd                                  |only
 keras3-0.2.0/keras3/man/op_depthwise_conv.Rd                                   |   17 
 keras3-0.2.0/keras3/man/op_det.Rd                                              |only
 keras3-0.2.0/keras3/man/op_diag.Rd                                             |   17 
 keras3-0.2.0/keras3/man/op_diagonal.Rd                                         |   17 
 keras3-0.2.0/keras3/man/op_diff.Rd                                             |   17 
 keras3-0.2.0/keras3/man/op_digitize.Rd                                         |   17 
 keras3-0.2.0/keras3/man/op_divide.Rd                                           |   40 
 keras3-0.2.0/keras3/man/op_divide_no_nan.Rd                                    |only
 keras3-0.2.0/keras3/man/op_dot.Rd                                              |   17 
 keras3-0.2.0/keras3/man/op_eig.Rd                                              |only
 keras3-0.2.0/keras3/man/op_einsum.Rd                                           |   35 
 keras3-0.2.0/keras3/man/op_elu.Rd                                              |   17 
 keras3-0.2.0/keras3/man/op_empty.Rd                                            |   17 
 keras3-0.2.0/keras3/man/op_equal.Rd                                            |   40 
 keras3-0.2.0/keras3/man/op_erf.Rd                                              |   16 
 keras3-0.2.0/keras3/man/op_erfinv.Rd                                           |only
 keras3-0.2.0/keras3/man/op_exp.Rd                                              |   17 
 keras3-0.2.0/keras3/man/op_expand_dims.Rd                                      |   17 
 keras3-0.2.0/keras3/man/op_expm1.Rd                                            |   17 
 keras3-0.2.0/keras3/man/op_extract_sequences.Rd                                |   16 
 keras3-0.2.0/keras3/man/op_eye.Rd                                              |   17 
 keras3-0.2.0/keras3/man/op_fft.Rd                                              |   16 
 keras3-0.2.0/keras3/man/op_fft2.Rd                                             |   16 
 keras3-0.2.0/keras3/man/op_flip.Rd                                             |   17 
 keras3-0.2.0/keras3/man/op_floor.Rd                                            |   17 
 keras3-0.2.0/keras3/man/op_floor_divide.Rd                                     |   40 
 keras3-0.2.0/keras3/man/op_fori_loop.Rd                                        |   16 
 keras3-0.2.0/keras3/man/op_full.Rd                                             |   17 
 keras3-0.2.0/keras3/man/op_full_like.Rd                                        |   17 
 keras3-0.2.0/keras3/man/op_gelu.Rd                                             |   17 
 keras3-0.2.0/keras3/man/op_get_item.Rd                                         |   17 
 keras3-0.2.0/keras3/man/op_greater.Rd                                          |   40 
 keras3-0.2.0/keras3/man/op_greater_equal.Rd                                    |   40 
 keras3-0.2.0/keras3/man/op_hard_sigmoid.Rd                                     |   17 
 keras3-0.2.0/keras3/man/op_hard_silu.Rd                                        |   17 
 keras3-0.2.0/keras3/man/op_hstack.Rd                                           |   17 
 keras3-0.2.0/keras3/man/op_identity.Rd                                         |   17 
 keras3-0.2.0/keras3/man/op_imag.Rd                                             |   17 
 keras3-0.2.0/keras3/man/op_image_affine_transform.Rd                           |   17 
 keras3-0.2.0/keras3/man/op_image_crop.Rd                                       |only
 keras3-0.2.0/keras3/man/op_image_extract_patches.Rd                            |   17 
 keras3-0.2.0/keras3/man/op_image_map_coordinates.Rd                            |   17 
 keras3-0.2.0/keras3/man/op_image_pad.Rd                                        |   17 
 keras3-0.2.0/keras3/man/op_image_resize.Rd                                     |   17 
 keras3-0.2.0/keras3/man/op_in_top_k.Rd                                         |   16 
 keras3-0.2.0/keras3/man/op_inv.Rd                                              |only
 keras3-0.2.0/keras3/man/op_irfft.Rd                                            |   16 
 keras3-0.2.0/keras3/man/op_is_tensor.Rd                                        |   16 
 keras3-0.2.0/keras3/man/op_isclose.Rd                                          |   17 
 keras3-0.2.0/keras3/man/op_isfinite.Rd                                         |   17 
 keras3-0.2.0/keras3/man/op_isinf.Rd                                            |   17 
 keras3-0.2.0/keras3/man/op_isnan.Rd                                            |   17 
 keras3-0.2.0/keras3/man/op_istft.Rd                                            |   16 
 keras3-0.2.0/keras3/man/op_leaky_relu.Rd                                       |   17 
 keras3-0.2.0/keras3/man/op_less.Rd                                             |   40 
 keras3-0.2.0/keras3/man/op_less_equal.Rd                                       |   40 
 keras3-0.2.0/keras3/man/op_linspace.Rd                                         |   17 
 keras3-0.2.0/keras3/man/op_log.Rd                                              |   17 
 keras3-0.2.0/keras3/man/op_log10.Rd                                            |   17 
 keras3-0.2.0/keras3/man/op_log1p.Rd                                            |   17 
 keras3-0.2.0/keras3/man/op_log2.Rd                                             |   17 
 keras3-0.2.0/keras3/man/op_log_sigmoid.Rd                                      |   17 
 keras3-0.2.0/keras3/man/op_log_softmax.Rd                                      |   17 
 keras3-0.2.0/keras3/man/op_logaddexp.Rd                                        |   17 
 keras3-0.2.0/keras3/man/op_logical_and.Rd                                      |   20 
 keras3-0.2.0/keras3/man/op_logical_not.Rd                                      |   19 
 keras3-0.2.0/keras3/man/op_logical_or.Rd                                       |   19 
 keras3-0.2.0/keras3/man/op_logical_xor.Rd                                      |   17 
 keras3-0.2.0/keras3/man/op_logspace.Rd                                         |   17 
 keras3-0.2.0/keras3/man/op_logsumexp.Rd                                        |   16 
 keras3-0.2.0/keras3/man/op_lu_factor.Rd                                        |only
 keras3-0.2.0/keras3/man/op_matmul.Rd                                           |   17 
 keras3-0.2.0/keras3/man/op_max.Rd                                              |   17 
 keras3-0.2.0/keras3/man/op_max_pool.Rd                                         |   17 
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Package databraryr updated to version 0.6.4 with previous version 0.6.3 dated 2024-03-26

Title: Interact with the 'Databrary.org' API
Description: 'Databrary.org' is a restricted access repository for research data, especially video and audio. This package provides commands to interact with the data stored on 'Databrary.org'.
Author: Rick O. Gilmore [aut, cre, cph], Jeffrey Spies [aut], National Science Foundation OAC-2032713 [fnd], National Institutes of Health R01HD094830 [fnd]
Maintainer: Rick O. Gilmore <rog1@psu.edu>

Diff between databraryr versions 0.6.3 dated 2024-03-26 and 0.6.4 dated 2024-04-18

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Package bayesROE updated to version 0.2 with previous version 0.1 dated 2023-03-09

Title: Bayesian Regions of Evidence
Description: Computation and visualization of Bayesian Regions of Evidence to systematically evaluate the sensitivity of a superiority or non-inferiority claim against any prior assumption of its assessors. Methodological details are elaborated by Hoefler and Miller (<https://osf.io/jxnsv>). Besides generic functions, the package also provides an intuitive 'Shiny' application, that can be run in local R environments.
Author: Robert Miller [cre, aut]
Maintainer: Robert Miller <robert.miller@tu-dresden.de>

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Package socialmixr updated to version 0.3.2 with previous version 0.3.1 dated 2023-10-26

Title: Social Mixing Matrices for Infectious Disease Modelling
Description: Provides methods for sampling contact matrices from diary data for use in infectious disease modelling, as discussed in Mossong et al. (2008) <doi:10.1371/journal.pmed.0050074>.
Author: Sebastian Funk [aut, cre], Lander Willem [aut], Hugo Gruson [aut], Maria Bekker-Nielsen Dunbar [ctb], Carl A. B. Pearson [ctb], Sam Clifford [ctb], Christopher Jarvis [ctb], Alexis Robert [ctb], Niel Hens [ctb], Pietro Coletti [col, dtm]
Maintainer: Sebastian Funk <sebastian.funk@lshtm.ac.uk>

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Package MBNMAdose updated to version 0.4.3 with previous version 0.4.2 dated 2023-08-08

Title: Dose-Response MBNMA Models
Description: Fits Bayesian dose-response model-based network meta-analysis (MBNMA) that incorporate multiple doses within an agent by modelling different dose-response functions, as described by Mawdsley et al. (2016) <doi:10.1002/psp4.12091>. By modelling dose-response relationships this can connect networks of evidence that might otherwise be disconnected, and can improve precision on treatment estimates. Several common dose-response functions are provided; others may be added by the user. Various characteristics and assumptions can be flexibly added to the models, such as shared class effects. The consistency of direct and indirect evidence in the network can be assessed using unrelated mean effects models and/or by node-splitting at the treatment level.
Author: Hugo Pedder [aut, cre] , Adil Karim [ctb]
Maintainer: Hugo Pedder <hugopedder@gmail.com>

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Package lokern updated to version 1.1-11 with previous version 1.1-10.1 dated 2023-12-07

Title: Kernel Regression Smoothing with Local or Global Plug-in Bandwidth
Description: Kernel regression smoothing with adaptive local or global plug-in bandwidth selection.
Author: Eva Herrmann <eherrmann@mathematik.tu-darmstadt.de> ; Packaged for R and enhanced by Martin Maechler
Maintainer: Martin Maechler <maechler@stat.math.ethz.ch>

Diff between lokern versions 1.1-10.1 dated 2023-12-07 and 1.1-11 dated 2024-04-18

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Package bibliometrix updated to version 4.2.0 with previous version 4.1.4 dated 2023-11-28

Title: Comprehensive Science Mapping Analysis
Description: Tool for quantitative research in scientometrics and bibliometrics. It provides various routines for importing bibliographic data from 'SCOPUS', 'Clarivate Analytics Web of Science' (<https://www.webofknowledge.com/>), 'Digital Science Dimensions' (<https://www.dimensions.ai/>), 'OpenAlex' (<https://openalex.org/>), 'Cochrane Library' (<https://www.cochranelibrary.com/>), 'Lens' (<https://lens.org>), and 'PubMed' (<https://pubmed.ncbi.nlm.nih.gov/>) databases, performing bibliometric analysis and building networks for co-citation, coupling, scientific collaboration and co-word analysis.
Author: Massimo Aria [cre, aut, cph] , Corrado Cuccurullo [aut]
Maintainer: Massimo Aria <aria@unina.it>

Diff between bibliometrix versions 4.1.4 dated 2023-11-28 and 4.2.0 dated 2024-04-18

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 R/authorProdOverTime.R                   |   42 
 R/bib2df.R                               |   24 
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 R/bradford.R                             |    7 
 R/cocMatrix.R                            |    7 
 R/cochrane2df.R                          |    9 
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 R/convert2df.R                           |   69 -
 R/couplingMap.R                          |   76 -
 R/csvLens2df.R                           |    7 
 R/csvOA2df.R                             |only
 R/csvScopus2df.R                         |   10 
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 R/histPlot.R                             |   53 
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 R/metaTagExtraction.R                    |    2 
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 R/net2VOSviewer.R                        |    2 
 R/networkPlot.R                          |    7 
 R/normalizeCItationScore.R               |   48 
 R/plot.bibliodendrogram.R                |    2 
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 R/plotThematicEvolution.R                |    3 
 R/pubmed2df.R                            |    9 
 R/rpys.R                                 |   47 
 R/splitCommunities.R                     |    9 
 R/summary.bibliometrix.R                 |    7 
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More information about bibliometrix at CRAN
Permanent link

Package stopp updated to version 0.2.3 with previous version 0.2.2 dated 2024-04-16

Title: Spatio-Temporal Point Pattern Methods, Model Fitting, Diagnostics, Simulation, Local Tests
Description: Toolbox for different kinds of spatio-temporal analyses to be performed on observed point patterns, following the growing stream of literature on point process theory. This R package implements functions to perform different kinds of analyses on point processes, proposed in the papers (Siino, Adelfio, and Mateu 2018<doi:10.1007/s00477-018-1579-0>; Siino et al. 2018<doi:10.1002/env.2463>; Adelfio et al. 2020<doi:10.1007/s00477-019-01748-1>; D’Angelo, Adelfio, and Mateu 2021<doi:10.1016/j.spasta.2021.100534>; D’Angelo, Adelfio, and Mateu 2022<doi:10.1007/s00362-022-01338-4>; D’Angelo, Adelfio, and Mateu 2023<doi:10.1016/j.csda.2022.107679>). The main topics include modeling, statistical inference, and simulation issues on spatio-temporal point processes on Euclidean space and linear networks.
Author: Nicoletta D'Angelo [aut, cre] , Giada Adelfio [aut]
Maintainer: Nicoletta D'Angelo <nicoletta.dangelo@unipa.it>

Diff between stopp versions 0.2.2 dated 2024-04-16 and 0.2.3 dated 2024-04-18

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 5 files changed, 16 insertions(+), 16 deletions(-)

More information about stopp at CRAN
Permanent link

Package geometa updated to version 0.8-0 with previous version 0.7-1 dated 2022-10-27

Title: Tools for Reading and Writing ISO/OGC Geographic Metadata
Description: Provides facilities to read, write and validate geographic metadata defined with ISO TC211 / OGC ISO geographic information metadata standards, and encoded using the ISO 19139 (XML) standard technical specification. This includes ISO 19110 (Feature cataloguing), 19115 (dataset metadata), 19119 (service metadata) and 19136 (GML). Other interoperable schemas from the OGC are progressively supported as well, such as the Sensor Web Enablement (SWE) Common Data Model, the OGC GML Coverage Implementation Schema (GMLCOV), or the OGC GML Referenceable Grid (GMLRGRID).
Author: Emmanuel Blondel [aut, cre]
Maintainer: Emmanuel Blondel <emmanuel.blondel1@gmail.com>

Diff between geometa versions 0.7-1 dated 2022-10-27 and 0.8-0 dated 2024-04-18

 DESCRIPTION                                                   |   22 
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 R/ISOCitation.R                                               |   10 
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 tests/testthat/test_ISOAssociationRole.R                      |    2 
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 tests/testthat/test_ISOFeatureType.R                          |    4 
 tests/testthat/test_ISOFreeText.R                             |   23 
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 tests/testthat/test_ISOKeywords.R                             |   35 
 tests/testthat/test_ISOLegalConstraints.R                     |   12 
 tests/testthat/test_ISOMetadata.R                             |   10 
 tests/testthat/test_ISOMultiplicity.R                         |    2 
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 84 files changed, 4640 insertions(+), 4449 deletions(-)

More information about geometa at CRAN
Permanent link

Package rpm updated to version 0.7-3 with previous version 0.7 dated 2023-04-21

Title: Modeling of Revealed Preferences Matchings
Description: Statistical estimation of revealed preference models from data collected on bipartite matchings. The models are for matchings within a bipartite population where individuals have utility for people based on known and unknown characteristics. People can form a partnership or remain unpartnered. The model represents both the availability of potential partners of different types and preferences of individuals for such people. The software estimates preference parameters based on sample survey data on partnerships and population composition. The simulation of matchings and goodness-of-fit are considered. See Goyal, Handcock, Jackson, Rendall and Yeung (2022) <doi:10.1093/jrsssa/qnad031>.
Author: Mark S. Handcock [aut, cre] , Ryan M. Admiraal [ctb], Fiona C. Yeung [ctb], Heide M. Jackson [ctb], Michael S. Rendall [ctb], Shuchi Goyal [ctb]
Maintainer: Mark S. Handcock <handcock@stat.ucla.edu>

Diff between rpm versions 0.7 dated 2023-04-21 and 0.7-3 dated 2024-04-18

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More information about rpm at CRAN
Permanent link

Package LexisNexisTools updated to version 1.0.0 with previous version 0.3.7 dated 2023-07-05

Title: Working with Files from 'LexisNexis'
Description: My PhD supervisor once told me that everyone doing newspaper analysis starts by writing code to read in files from the 'LexisNexis' newspaper archive (retrieved e.g., from <https://www.lexisnexis.com/> or any of the partner sites). However, while this is a nice exercise I do recommend, not everyone has the time. This package takes files downloaded from the newspaper archive of 'LexisNexis', reads them into R and offers functions for further processing.
Author: Johannes B. Gruber [aut, cre]
Maintainer: Johannes B. Gruber <JohannesB.Gruber@gmail.com>

Diff between LexisNexisTools versions 0.3.7 dated 2023-07-05 and 1.0.0 dated 2024-04-18

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Permanent link

Package explainer updated to version 1.0.1 with previous version 1.0.0 dated 2023-12-15

Title: Machine Learning Model Explainer
Description: It enables detailed interpretation of complex classification and regression models through Shapley analysis including data-driven characterization of subgroups of individuals. Furthermore, it facilitates multi-measure model evaluation, model fairness, and decision curve analysis. Additionally, it offers enhanced visualizations with interactive elements.
Author: Ramtin Zargari Marandi [aut, cre]
Maintainer: Ramtin Zargari Marandi <ramtin.zargari.marandi@regionh.dk>

Diff between explainer versions 1.0.0 dated 2023-12-15 and 1.0.1 dated 2024-04-18

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Package bliss updated to version 1.0.5 with previous version 1.0.4 dated 2022-02-16

Title: Bayesian Functional Linear Regression with Sparse Step Functions
Description: A method for the Bayesian functional linear regression model (scalar-on-function), including two estimators of the coefficient function and an estimator of its support. A representation of the posterior distribution is also available. Grollemund P-M., Abraham C., Baragatti M., Pudlo P. (2019) <doi:10.1214/18-BA1095>.
Author: Paul-Marie Grollemund [aut, cre], Isabelle Sanchez [ctr], Meili Baragatti [ctr]
Maintainer: Paul-Marie Grollemund <paul.marie.grollemund@gmail.com>

Diff between bliss versions 1.0.4 dated 2022-02-16 and 1.0.5 dated 2024-04-18

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More information about bliss at CRAN
Permanent link

Package ClickHouseHTTP updated to version 0.3.3 with previous version 0.3.2 dated 2023-07-04

Title: A Simple HTTP Database Interface to 'ClickHouse'
Description: 'ClickHouse' (<https://clickhouse.com/>) is an open-source, high performance columnar OLAP (online analytical processing of queries) database management system for real-time analytics using SQL. This 'DBI' backend relies on the 'ClickHouse' HTTP interface and support HTTPS protocol.
Author: Patrice Godard [aut, cre, cph], Eusebiu Marcu [ctb]
Maintainer: Patrice Godard <patrice.godard@gmail.com>

Diff between ClickHouseHTTP versions 0.3.2 dated 2023-07-04 and 0.3.3 dated 2024-04-18

 DESCRIPTION |    8 ++++----
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More information about ClickHouseHTTP at CRAN
Permanent link

Wed, 17 Apr 2024

Package dst updated to version 1.6.0 with previous version 1.5.2 dated 2023-11-16

Title: Using the Theory of Belief Functions
Description: Using the Theory of Belief Functions for evidence calculus. Basic probability assignments, or mass functions, can be defined on the subsets of a set of possible values and combined. A mass function can be extended to a larger frame. Marginalization, i.e. reduction to a smaller frame can also be done. These features can be combined to analyze small belief networks and take into account situations where information cannot be satisfactorily described by probability distributions.
Author: Claude Boivin <webapp.cb@gmail.com> Peiyuan Zhu <garyzhubc@gmail.com>
Maintainer: Claude Boivin <webapp.cb@gmail.com>

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Package POSTm updated to version 1.4 with previous version 1.3 dated 2023-12-13

Title: Phylogeny-Guided OTU-Specific Association Test for Microbiome Data
Description: Implements the Phylogeny-Guided Microbiome OTU-Specific Association Test method, which boosts the testing power by adaptively borrowing information from phylogenetically close OTUs (operational taxonomic units) of the target OTU. This method is built on a kernel machine regression framework and allows for flexible modeling of complex microbiome effects, adjustments for covariates, and can accommodate both continuous and binary outcomes.
Author: Caizhi Huang [aut], Jung-Ying Tzeng [aut], Shannon T. Holloway [aut, cre]
Maintainer: Shannon T. Holloway <shannon.t.holloway@gmail.com>

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Package fixest updated to version 0.12.0 with previous version 0.11.2 dated 2023-11-24

Title: Fast Fixed-Effects Estimations
Description: Fast and user-friendly estimation of econometric models with multiple fixed-effects. Includes ordinary least squares (OLS), generalized linear models (GLM) and the negative binomial. The core of the package is based on optimized parallel C++ code, scaling especially well for large data sets. The method to obtain the fixed-effects coefficients is based on Berge (2018) <https://github.com/lrberge/fixest/blob/master/_DOCS/FENmlm_paper.pdf>. Further provides tools to export and view the results of several estimations with intuitive design to cluster the standard-errors.
Author: Laurent Berge [aut, cre], Sebastian Krantz [ctb], Grant McDermott [ctb] , Russell Lenth [ctb]
Maintainer: Laurent Berge <laurent.berge@u-bordeaux.fr>

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Package BayesSUR updated to version 2.1-7 with previous version 2.1-6 dated 2024-01-09

Title: Bayesian Seemingly Unrelated Regression
Description: Bayesian seemingly unrelated regression with general variable selection and dense/sparse covariance matrix. The sparse seemingly unrelated regression is described in Bottolo et al. (2021) <doi:10.1111/rssc.12490>, the software paper is in Zhao et al. (2021) <doi:10.18637/jss.v100.i11>, and the model with random effects is described in Zhao et al. (2024) <doi:10.1093/jrsssc/qlad102>.
Author: Marco Banterle [aut], Zhi Zhao [aut, cre], Leonardo Bottolo [ctb], Sylvia Richardson [ctb], Waldir Leoncio [ctb], Alex Lewin [aut], Manuela Zucknick [aut]
Maintainer: Zhi Zhao <zhi.zhao@medisin.uio.no>

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Package seriation updated to version 1.5.5 with previous version 1.5.4 dated 2023-12-12

Title: Infrastructure for Ordering Objects Using Seriation
Description: Infrastructure for ordering objects with an implementation of several seriation/sequencing/ordination techniques to reorder matrices, dissimilarity matrices, and dendrograms. Also provides (optimally) reordered heatmaps, color images and clustering visualizations like dissimilarity plots, and visual assessment of cluster tendency plots (VAT and iVAT). Hahsler et al (2008) <doi:10.18637/jss.v025.i03>.
Author: Michael Hahsler [aut, cre, cph] , Christian Buchta [aut, cph], Kurt Hornik [aut, cph] , David Barnett [ctb], Michael Brusco [ctb, cph], Michael Friendly [ctb], Hans-Friedrich Koehn [ctb, cph], Fionn Murtagh [ctb, cph], Stephanie Stahl [ctb, cph]
Maintainer: Michael Hahsler <mhahsler@lyle.smu.edu>

Diff between seriation versions 1.5.4 dated 2023-12-12 and 1.5.5 dated 2024-04-17

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Package tolerance updated to version 3.0.0 with previous version 2.0.0 dated 2020-02-05

Title: Statistical Tolerance Intervals and Regions
Description: Statistical tolerance limits provide the limits between which we can expect to find a specified proportion of a sampled population with a given level of confidence. This package provides functions for estimating tolerance limits (intervals) for various univariate distributions (binomial, Cauchy, discrete Pareto, exponential, two-parameter exponential, extreme value, hypergeometric, Laplace, logistic, negative binomial, negative hypergeometric, normal, Pareto, Poisson-Lindley, Poisson, uniform, and Zipf-Mandelbrot), Bayesian normal tolerance limits, multivariate normal tolerance regions, nonparametric tolerance intervals, tolerance bands for regression settings (linear regression, nonlinear regression, nonparametric regression, and multivariate regression), and analysis of variance tolerance intervals. Visualizations are also available for most of these settings.
Author: Derek S. Young [aut, cre] , Kedai Cheng [aut]
Maintainer: Derek S. Young <derek.young@uky.edu>

Diff between tolerance versions 2.0.0 dated 2020-02-05 and 3.0.0 dated 2024-04-17

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Package adaptivetau updated to version 2.3-1 with previous version 2.3 dated 2023-11-28

Title: Tau-Leaping Stochastic Simulation
Description: Implements adaptive tau leaping to approximate the trajectory of a continuous-time stochastic process as described by Cao et al. (2007) The Journal of Chemical Physics <doi:10.1063/1.2745299> (aka. the Gillespie stochastic simulation algorithm). This package is based upon work supported by NSF DBI-0906041 and NIH K99-GM104158 to Philip Johnson and NIH R01-AI049334 to Rustom Antia.
Author: Philip Johnson
Maintainer: Philip Johnson <plfj@umd.edu>

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Package modsem updated to version 0.1.2 with previous version 0.1.1 dated 2024-04-15

Title: Latent Interaction (and Moderation) Analysis in Structural Equation Models (SEM)
Description: Estimation of interaction (i.e., moderation) effects between latent variables in structural equation models (SEM). The supported methods are: The constrained approach (Algina & Moulder, 2001). The unconstrained approach (Marsh et al., 2004). The residual centering approach (Little et al., 2006). The double centering approach (Lin et al., 2010). The latent moderated structural equations (LMS) approach (Klein & Moosbrugger, 2000). The quasi-maximum likelihood (QML) approach (Klein & Muthén, 2007) (temporarily unavailable) The constrained- unconstrained, residual- and double centering- approaches are estimated via 'lavaan' (Rosseel, 2012), whilst the LMS- and QML- approaches are estimated via by ModSEM it self. Alternatively model can be estimated via 'Mplus' (Muthén & Muthén, 1998-2017). References: Algina, J., & Moulder, B. C. (2001). <doi:10.1207/S15328007SEM0801_3>. "A note on estimating the Jöreskog-Yang model for latent variable interaction using 'LISREL' 8 [...truncated...]
Author: Kjell Solem Slupphaug [aut, cre]
Maintainer: Kjell Solem Slupphaug <slupphaugkjell@gmail.com>

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Package jagstargets updated to version 1.2.0 with previous version 1.1.0 dated 2023-01-06

Title: Targets for JAGS Pipelines
Description: Bayesian data analysis usually incurs long runtimes and cumbersome custom code. A pipeline toolkit tailored to Bayesian statisticians, the 'jagstargets' R package is leverages 'targets' and 'R2jags' to ease this burden. 'jagstargets' makes it super easy to set up scalable JAGS pipelines that automatically parallelize the computation and skip expensive steps when the results are already up to date. Minimal custom code is required, and there is no need to manually configure branching, so usage is much easier than 'targets' alone. For the underlying methodology, please refer to the documentation of 'targets' <doi:10.21105/joss.02959> and 'JAGS' (Plummer 2003) <https://www.r-project.org/conferences/DSC-2003/Proceedings/Plummer.pdf>.
Author: William Michael Landau [aut, cre] , David Lawrence Miller [rev], Eli Lilly and Company [cph]
Maintainer: William Michael Landau <will.landau.oss@gmail.com>

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Package iNEXT.beta3D updated to version 1.0.2 with previous version 1.0.1 dated 2024-03-25

Title: Interpolation and Extrapolation with Beta Diversity for Three Dimensions of Biodiversity
Description: As a sequel to 'iNEXT', the 'iNEXT.beta3D' package provides functions to compute standardized taxonomic, phylogenetic, and functional diversity (3D) estimates with a common sample size (for alpha and gamma diversity) or sample coverage (for alpha, beta, gamma diversity as well as dissimilarity or turnover indices). Hill numbers and their generalizations are used to quantify 3D and to make multiplicative decomposition (gamma = alpha x beta). The package also features size- and coverage-based rarefaction and extrapolation sampling curves to facilitate rigorous comparison of beta diversity across datasets. See Chao et al. (2023) <doi:10.1002/ecm.1588> for more details.
Author: Anne Chao [aut, cre], KaiHsiang Hu [ctb]
Maintainer: Anne Chao <chao@stat.nthu.edu.tw>

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Package ecoregime updated to version 0.2.0 with previous version 0.1.3 dated 2023-09-10

Title: Analysis of Ecological Dynamic Regimes
Description: A toolbox for implementing the Ecological Dynamic Regime framework (Sánchez-Pinillos et al., 2023 <doi:10.1002/ecm.1589>) to characterize and compare groups of ecological trajectories in multidimensional spaces defined by state variables. The package includes the RETRA-EDR algorithm to identify representative trajectories, functions to generate, summarize, and visualize representative trajectories, and several metrics to quantify the distribution and heterogeneity of trajectories in an ecological dynamic regime and quantify the dissimilarity between two or more ecological dynamic regimes. The package also includes a set of functions to assess ecological resilience based on ecological dynamic regimes (Sánchez-Pinillos et al., 2024 <doi:10.1016/j.biocon.2023.110409>).
Author: Martina Sanchez-Pinillos [aut, cre, cph]
Maintainer: Martina Sanchez-Pinillos <martina.sanchez.pinillos@gmail.com>

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Package adbcsqlite updated to version 0.11.0.1 with previous version 0.10.0 dated 2024-02-22

Title: 'Arrow' Database Connectivity ('ADBC') 'SQLite' Driver
Description: Provides a developer-facing interface to the 'Arrow' Database Connectivity ('ADBC') 'SQLite' driver for the purposes of building high-level database interfaces for users. 'ADBC' <https://arrow.apache.org/adbc/> is an API standard for database access libraries that uses 'Arrow' for result sets and query parameters.
Author: Dewey Dunnington [aut, cre] , Apache Arrow [aut, cph], Apache Software Foundation [cph]
Maintainer: Dewey Dunnington <dewey@dunnington.ca>

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Package tclust updated to version 2.0-3 with previous version 1.5-6 dated 2024-02-09

Title: Robust Trimmed Clustering
Description: Provides functions for robust trimmed clustering. The methods are described in Garcia-Escudero (2008) <doi:10.1214/07-AOS515>, Fritz et al. (2012) <doi:10.18637/jss.v047.i12>, Garcia-Escudero et al. (2011) <doi:10.1007/s11222-010-9194-z> and others.
Author: Valentin Todorov [aut, cre] , Luis Angel Garcia Escudero [aut], Agustin Mayo Iscar [aut], Javier Crespo Guerrero [aut], Heinrich Fritz [aut]
Maintainer: Valentin Todorov <valentin.todorov@chello.at>

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Package nlive updated to version 0.3.0 with previous version 0.2.0 dated 2023-10-30

Title: Automated Estimation of Sigmoidal and Piecewise Linear Mixed Models
Description: Estimation of relatively complex nonlinear mixed-effects models, including the Sigmoidal Mixed Model and the Piecewise Linear Mixed Model with abrupt or smooth transition, through a single intuitive line of code and with automated generation of starting values.
Author: Maude Wagner [aut, cre] , Emmanuelle Comets [ctb], Ana W. Capuano [aut]
Maintainer: Maude Wagner <maude_wagner@rush.edu>

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Package targets updated to version 1.7.0 with previous version 1.6.0 dated 2024-03-13

Title: Dynamic Function-Oriented 'Make'-Like Declarative Pipelines
Description: Pipeline tools coordinate the pieces of computationally demanding analysis projects. The 'targets' package is a 'Make'-like pipeline tool for statistics and data science in R. The package skips costly runtime for tasks that are already up to date, orchestrates the necessary computation with implicit parallel computing, and abstracts files as R objects. If all the current output matches the current upstream code and data, then the whole pipeline is up to date, and the results are more trustworthy than otherwise. The methodology in this package borrows from GNU 'Make' (2015, ISBN:978-9881443519) and 'drake' (2018, <doi:10.21105/joss.00550>).
Author: William Michael Landau [aut, cre] , Matthew T. Warkentin [ctb], Mark Edmondson [ctb] , Samantha Oliver [rev] , Tristan Mahr [rev] , Eli Lilly and Company [cph]
Maintainer: William Michael Landau <will.landau.oss@gmail.com>

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Package tarchetypes updated to version 0.9.0 with previous version 0.8.0 dated 2024-03-18

Title: Archetypes for Targets
Description: Function-oriented Make-like declarative pipelines for Statistics and data science are supported in the 'targets' R package. As an extension to 'targets', the 'tarchetypes' package provides convenient user-side functions to make 'targets' easier to use. By establishing reusable archetypes for common kinds of targets and pipelines, these functions help express complicated reproducible pipelines concisely and compactly. The methods in this package were influenced by the 'drake' R package by Will Landau (2018) <doi:10.21105/joss.00550>.
Author: William Michael Landau [aut, cre] , Samantha Oliver [rev] , Tristan Mahr [rev] , Eli Lilly and Company [cph]
Maintainer: William Michael Landau <will.landau.oss@gmail.com>

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Package qoi updated to version 0.1.0 with previous version 0.0.4 dated 2023-02-07

Title: Read and Write QOI Images
Description: The new QOI file format offers a very simple but efficient image compression algorithm. This package provides an easy and simple way to read, write and display bitmap images stored in the QOI (Quite Ok Image) format. It can read and write both files and in-memory raw vectors.
Author: Johannes Friedrich [aut, trl, cre], Dominic Szablewski [cph]
Maintainer: Johannes Friedrich <Johannes.Friedrich@posteo.de>

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Package aspace updated to version 4.1.1 with previous version 4.1.0 dated 2023-09-05

Title: Functions for Estimating Centrographic Statistics
Description: A collection of functions for computing centrographic statistics (e.g., standard distance, standard deviation ellipse, standard deviation box) for observations taken at point locations. Separate plotting functions have been developed for each measure. Users interested in writing results to ESRI shapefiles can do so by using results from 'aspace' functions as inputs to the convert.to.shapefile() and write.shapefile() functions in the 'shapefiles' library. We intend to provide 'terra' integration for geographic data in a future release. The 'aspace' package was originally conceived to aid in the analysis of spatial patterns of travel behaviour (see Buliung and Remmel 2008 <doi:10.1007/s10109-008-0063-7>).
Author: Tarmo K. Remmel [aut, cre] , Randy Bui [aut], Ron N. Buliung [aut]
Maintainer: Tarmo K. Remmel <remmelt@yorku.ca>

Diff between aspace versions 4.1.0 dated 2023-09-05 and 4.1.1 dated 2024-04-17

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Package RQdeltaCT updated to version 1.3.0 with previous version 1.2.1 dated 2024-04-02

Title: Relative Quantification of Gene Expression using Delta Ct Methods
Description: The commonly used methods for relative quantification of gene expression levels obtained in real-time PCR (Polymerase Chain Reaction) experiments are the delta Ct methods, encompassing 2^-dCt and 2^-ddCt methods, originally proposed by Kenneth J. Livak and Thomas D. Schmittgen (2001) <doi:10.1006/meth.2001.1262>. The main idea is to normalise gene expression values using endogenous control gene, present gene expression levels in linear form by using the 2^-(value)^ transformation, and calculate differences in gene expression levels between groups of samples (or technical replicates of a single sample). The 'RQdeltaCT' package offers functions that cover both methods for comparison of either independent groups of samples or groups with paired samples, together with importing expression datasets, performing multi-step quality control of data, enabling numerous data visualisations, enrichment of the standard workflow with additional useful analyses (correlation analysis, Receiver Op [...truncated...]
Author: Daniel Zalewski [aut, cre]
Maintainer: Daniel Zalewski <daniel.piotr.zalewski@gmail.com>

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Package XLConnect updated to version 1.0.9 with previous version 1.0.8 dated 2024-01-30

Title: Excel Connector for R
Description: Provides comprehensive functionality to read, write and format Excel data.
Author: Mirai Solutions GmbH [aut], Martin Studer [cre], The Apache Software Foundation [ctb, cph] , Graph Builder [ctb, cph] , Brett Woolridge [ctb, cph]
Maintainer: Martin Studer <martin.studer@mirai-solutions.com>

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Package tbm updated to version 0.3-6 with previous version 0.3-5 dated 2022-01-14

Title: Transformation Boosting Machines
Description: Boosting the likelihood of conditional and shift transformation models as introduced in \doi{10.1007/s11222-019-09870-4}.
Author: Torsten Hothorn [aut, cre]
Maintainer: Torsten Hothorn <Torsten.Hothorn@R-project.org>

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Package mlr3spatiotempcv updated to version 2.3.1 with previous version 2.3.0 dated 2024-01-22

Title: Spatiotemporal Resampling Methods for 'mlr3'
Description: Extends the mlr3 ML framework with spatio-temporal resampling methods to account for the presence of spatiotemporal autocorrelation (STAC) in predictor variables. STAC may cause highly biased performance estimates in cross-validation if ignored.
Author: Patrick Schratz [aut, cre] , Marc Becker [aut] , Jannes Muenchow [ctb] , Michel Lang [ctb]
Maintainer: Patrick Schratz <patrick.schratz@gmail.com>

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Package shinyWidgets updated to version 0.8.5 with previous version 0.8.4 dated 2024-04-04

Title: Custom Inputs Widgets for Shiny
Description: Collection of custom input controls and user interface components for 'Shiny' applications. Give your applications a unique and colorful style !
Author: Victor Perrier [aut, cre, cph], Fanny Meyer [aut], David Granjon [aut], Ian Fellows [ctb] , Wil Davis [ctb] , Spencer Matthews [ctb] , JavaScript and CSS libraries authors [ctb, cph]
Maintainer: Victor Perrier <victor.perrier@dreamrs.fr>

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Package thurstonianIRT updated to version 0.12.5 with previous version 0.12.4 dated 2023-12-19

Title: Thurstonian IRT Models
Description: Fit Thurstonian Item Response Theory (IRT) models in R. This package supports fitting Thurstonian IRT models and its extensions using 'Stan', 'lavaan', or 'Mplus' for the model estimation. Functionality for extracting results, making predictions, and simulating data is provided as well. References: Brown & Maydeu-Olivares (2011) <doi:10.1177/0013164410375112>; Bürkner et al. (2019) <doi:10.1177/0013164419832063>.
Author: Paul-Christian Buerkner [aut, cre], Angus Hughes [ctb], Trustees of Columbia University [cph]
Maintainer: Paul-Christian Buerkner <paul.buerkner@gmail.com>

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Package permChacko updated to version 1.0.0 with previous version 0.2.0 dated 2023-11-07

Title: Chacko Test for Order-Restriction with Permutation
Description: Implements an extension of the Chacko chi-square test for ordered vectors (Chacko, 1966, <https://www.jstor.org/stable/25051572>). Our extension brings the Chacko test to the computer age by implementing a permutation test to offer a numeric estimate of the p-value, which is particularly useful when the analytic solution is not available.
Author: Waldir Leoncio [aut, cre] , Graeme Ruxton [aut], Morten Wang Fagerland [aut]
Maintainer: Waldir Leoncio <w.l.netto@medisin.uio.no>

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Package nngeo updated to version 0.4.8 with previous version 0.4.7 dated 2023-04-24

Title: k-Nearest Neighbor Join for Spatial Data
Description: K-nearest neighbor search for projected and non-projected 'sf' spatial layers. Nearest neighbor search uses (1) C code from 'GeographicLib' for lon-lat point layers, (2) function knn() from package 'nabor' for projected point layers, or (3) function st_distance() from package 'sf' for line or polygon layers. The package also includes several other utility functions for spatial analysis.
Author: Michael Dorman [aut, cre], Johnathan Rush [ctb], Ian Hough [ctb], Dominic Russel [ctb], Luigi Ranghetti [ctb], Attilio Benini [ctb], Arnaud Tarroux [ctb], Felipe Matas [ctb], Charles F.F Karney [ctb, cph]
Maintainer: Michael Dorman <dorman@post.bgu.ac.il>

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Package inferCSN updated to version 1.0.3 with previous version 1.0.1 dated 2024-03-15

Title: Inferring Cell-Specific Gene Regulatory Network
Description: A method for inferring cell-specific gene regulatory network from single-cell sequencing data.
Author: Meng Xu [aut, cre]
Maintainer: Meng Xu <mengxu98@qq.com>

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Package tern updated to version 0.9.4 with previous version 0.9.3 dated 2023-12-08

Title: Create Common TLGs Used in Clinical Trials
Description: Table, Listings, and Graphs (TLG) library for common outputs used in clinical trials.
Author: Joe Zhu [aut, cre], Daniel Sabanes Bove [aut], Jana Stoilova [aut], Davide Garolini [aut], Emily de la Rua [aut], Abinaya Yogasekaram [aut], Heng Wang [aut], Francois Collin [aut], Adrian Waddell [aut], Pawel Rucki [aut], Chendi Liao [aut], Jennifer [...truncated...]
Maintainer: Joe Zhu <joe.zhu@roche.com>

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Package SubtypeDrug updated to version 0.1.9 with previous version 0.1.8 dated 2024-03-18

Title: Prioritization of Candidate Cancer Subtype Specific Drugs
Description: A systematic biology tool was developed to prioritize cancer subtype-specific drugs by integrating genetic perturbation, drug action, biological pathway, and cancer subtype. The capabilities of this tool include inferring patient-specific subpathway activity profiles in the context of gene expression profiles with subtype labels, calculating differentially expressed subpathways based on cultured human cells treated with drugs in the 'cMap' (connectivity map) database, prioritizing cancer subtype specific drugs according to drug-disease reverse association score based on subpathway, and visualization of results (Castelo (2013) <doi:10.1186/1471-2105-14-7>; Han et al (2019) <doi:10.1093/bioinformatics/btz894>; Lamb and Justin (2006) <doi:10.1126/science.1132939>). Please cite using <doi:10.1093/bioinformatics/btab011>.
Author: Xudong Han, Junwei Han, Chonghui Liu
Maintainer: Junwei Han <hanjunwei1981@163.com>

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Package planr updated to version 0.4.0 with previous version 0.3.0 dated 2024-01-21

Title: Tools for Supply Chain Management, Demand and Supply Planning
Description: Perform flexible and quick calculations for Demand and Supply Planning, such as projected inventories and coverages, as well as replenishment plan. For any time bucket, daily, weekly or monthly, and any granularity level, product or group of products.
Author: Nicolas Nguyen [aut, cre]
Maintainer: Nicolas Nguyen <nikonguyen@yahoo.fr>

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Package ntsDists updated to version 2.1.1 with previous version 2.1.0 dated 2024-04-14

Title: Neutrosophic Distributions
Description: Computes the pdf, cdf, quantile function and generating random numbers for neutrosophic distributions. This family have been developed by different authors in the recent years. See Patro and Smarandache (2016) <doi:10.5281/zenodo.571153> and Rao et al (2023) <doi:10.5281/zenodo.7832786>.
Author: Danial Mazarei [aut, cre] , Mina Norouzirad [aut] , Amin Roshani [aut] , Gadde Srinivasa Rao [ctb] , Foad Esmaeili [ctb] , FCT, I.P. [fnd] )
Maintainer: Danial Mazarei <danial.mazarei@gmail.com>

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Package ggfortify updated to version 0.4.17 with previous version 0.4.16 dated 2023-03-19

Title: Data Visualization Tools for Statistical Analysis Results
Description: Unified plotting tools for statistics commonly used, such as GLM, time series, PCA families, clustering and survival analysis. The package offers a single plotting interface for these analysis results and plots in a unified style using 'ggplot2'.
Author: Masaaki Horikoshi [aut], Yuan Tang [aut, cre] , Austin Dickey [ctb], Matthias Grenie [ctb], Ryan Thompson [ctb], Luciano Selzer [ctb], Dario Strbenac [ctb], Kirill Voronin [ctb], Damir Pulatov [ctb]
Maintainer: Yuan Tang <terrytangyuan@gmail.com>

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Tue, 16 Apr 2024

Package spmodel updated to version 0.6.0 with previous version 0.5.1 dated 2024-01-09

Title: Spatial Statistical Modeling and Prediction
Description: Fit, summarize, and predict for a variety of spatial statistical models applied to point-referenced and areal (lattice) data. Parameters are estimated using various methods. Additional modeling features include anisotropy, non-spatial random effects, partition factors, big data approaches, and more. Model-fit statistics are used to summarize, visualize, and compare models. Predictions at unobserved locations are readily obtainable. For additional details, see Dumelle et al. (2023) <doi:10.1371/journal.pone.0282524>.
Author: Michael Dumelle [aut, cre] , Matt Higham [aut], Jay M. Ver Hoef [aut]
Maintainer: Michael Dumelle <Dumelle.Michael@epa.gov>

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Package locuszoomr updated to version 0.3.0 with previous version 0.2.1 dated 2024-02-17

Title: Gene Locus Plot with Gene Annotations
Description: Publication-ready regional gene locus plots similar to those produced by the web interface 'LocusZoom' <https://my.locuszoom.org>, but running locally in R. Genetic or genomic data with gene annotation tracks are plotted via R base graphics, 'ggplot2' or 'plotly', allowing flexibility and easy customisation including laying out multiple locus plots on the same page. It uses the 'LDlink' API <https://ldlink.nih.gov/?tab=apiaccess> to query linkage disequilibrium data from the 1000 Genomes Project and can overlay this on plots.
Author: Myles Lewis [aut, cre]
Maintainer: Myles Lewis <myles.lewis@qmul.ac.uk>

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Package tram updated to version 1.0-3 with previous version 1.0-2 dated 2024-01-30

Title: Transformation Models
Description: Formula-based user-interfaces to specific transformation models implemented in package 'mlt'. Available models include Cox models, some parametric survival models (Weibull, etc.), models for ordered categorical variables, normal and non-normal (Box-Cox type) linear models, and continuous outcome logistic regression (Lohse et al., 2017, <DOI:10.12688/f1000research.12934.1>). The underlying theory is described in Hothorn et al. (2018) <DOI:10.1111/sjos.12291>. An extension to transformation models for clustered data is provided (Barbanti and Hothorn, 2022, <DOI:10.1093/biostatistics/kxac048>). Multivariate conditional transformation models (Klein et al, 2022, <DOI:10.1111/sjos.12501>) and shift-scale transformation models (Siegfried et al, 2023, <DOI:10.1080/00031305.2023.2203177>) can be fitted as well.
Author: Torsten Hothorn [aut, cre] , Luisa Barbanti [aut] , Sandra Siegfried [aut] , Brian Ripley [ctb], Bill Venables [ctb], Douglas M. Bates [ctb], Nadja Klein [ctb]
Maintainer: Torsten Hothorn <Torsten.Hothorn@R-project.org>

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Package symptomcheckR updated to version 0.1.3 with previous version 0.1.1 dated 2024-01-12

Title: Analyzing and Visualizing Symptom Checker Performance
Description: Easily analyze and visualize the performance of symptom checkers. This package can be used to gain comprehensive insights into the performance of single symptom checkers or the performance of multiple symptom checkers. It can be used to easily compare these symptom checkers across several metrics to gain an understanding of their strengths and weaknesses. The metrics are developed in Kopka et al. (2023) <doi:10.1177/20552076231194929>.
Author: Marvin Kopka [cre, aut] , Malte L. Schmieding [aut] , Markus A. Feufel [aut]
Maintainer: Marvin Kopka <marvin.kopka@tu-berlin.de>

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Package statGraph updated to version 1.0.0 with previous version 0.5.1 dated 2024-01-25

Title: Statistical Methods for Graphs
Description: Contains statistical methods to analyze graphs, such as graph parameter estimation, model selection based on the Graph Information Criterion, statistical tests to discriminate two or more populations of graphs, correlation between graphs, and clustering of graphs. References: Takahashi et al. (2012) <doi:10.1371/journal.pone.0049949>, Fujita et al. (2017) <doi:10.3389/fnins.2017.00066>, Fujita et al. (2017) <doi:10.1016/j.csda.2016.11.016>, Fujita et al. (2019) <doi:10.1093/comnet/cnz028>.
Author: Grover E. Castro Guzman [aut], Diogo R. da Costa [aut], Taiane C. Ramos [aut], Suzana S. Santos [aut], Eduardo S. Lira [aut], Andre Fujita [aut, cre]
Maintainer: Andre Fujita <andrefujita@usp.br>

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Package REDCapTidieR updated to version 1.1.1 with previous version 1.1.0 dated 2024-03-28

Title: Extract 'REDCap' Databases into Tidy 'Tibble's
Description: Convert 'REDCap' exports into tidy tables for easy handling of 'REDCap' repeat instruments and event arms.
Author: Richard Hanna [aut, cre] , Stephan Kadauke [aut] , Ezra Porter [aut]
Maintainer: Richard Hanna <richardshanna91@gmail.com>

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Package unikn updated to version 1.0.0 with previous version 0.9.0 dated 2023-08-10

Title: Graphical Elements of the University of Konstanz's Corporate Design
Description: Define and use graphical elements of corporate design manuals in R. The 'unikn' package provides color functions (by defining dedicated colors and color palettes, and commands for finding, changing, viewing, and using them) and styled text elements (e.g., for marking, underlining, or plotting colored titles). The pre-defined range of colors and text decoration functions is based on the corporate design of the University of Konstanz <https://www.uni-konstanz.de/>, but can be adapted and extended for other purposes or institutions.
Author: Hansjoerg Neth [aut, cre] , Nico Gradwohl [aut]
Maintainer: Hansjoerg Neth <h.neth@uni.kn>

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Package sassy updated to version 1.2.4 with previous version 1.2.3 dated 2024-02-07

Title: Makes 'R' Easier for Everyone
Description: A meta-package that aims to make 'R' easier for everyone, especially programmers who have a background in 'SAS®' software. This set of packages brings many useful concepts to 'R', including data libraries, data dictionaries, formats and format catalogs, a data step, and a traceable log. The 'flagship' package is a reporting package that can output in text, rich text, 'PDF', 'HTML', and 'DOCX' file formats.
Author: David J. Bosak
Maintainer: David Bosak <dbosak01@gmail.com>

Diff between sassy versions 1.2.3 dated 2024-02-07 and 1.2.4 dated 2024-04-16

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Package optparse updated to version 1.7.5 with previous version 1.7.4 dated 2024-01-16

Title: Command Line Option Parser
Description: A command line parser inspired by Python's 'optparse' library to be used with Rscript to write "#!" shebang scripts that accept short and long flag/options.
Author: Trevor L. Davis [aut, cre] , Allen Day [ctb] , Python Software Foundation [ctb] , Steve Lianoglou [ctb], Jim Nikelski [ctb], Kirill Mueller [ctb], Peter Humburg [ctb], Rich FitzJohn [ctb], Gyu Jin Choi [ctb]
Maintainer: Trevor L. Davis <trevor.l.davis@gmail.com>

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Package diffusion updated to version 0.4.0 with previous version 0.2.7 dated 2018-01-05

Title: Forecast the Diffusion of New Products
Description: Various diffusion models to forecast new product growth. Currently the package contains Bass, Gompertz, Gamma/Shifted Gompertz and Weibull curves. See Meade and Islam (2006) <doi:10.1016/j.ijforecast.2006.01.005>.
Author: Oliver Schaer [aut, cre] , Nikolaos Kourentzes [aut] , Ivan Svetunkov [aut]
Maintainer: Oliver Schaer <info@oliverschaer.ch>

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