Tue, 19 Nov 2024

Package spatstat updated to version 3.3-0 with previous version 3.2-1 dated 2024-09-22

Title: Spatial Point Pattern Analysis, Model-Fitting, Simulation, Tests
Description: Comprehensive open-source toolbox for analysing Spatial Point Patterns. Focused mainly on two-dimensional point patterns, including multitype/marked points, in any spatial region. Also supports three-dimensional point patterns, space-time point patterns in any number of dimensions, point patterns on a linear network, and patterns of other geometrical objects. Supports spatial covariate data such as pixel images. Contains over 3000 functions for plotting spatial data, exploratory data analysis, model-fitting, simulation, spatial sampling, model diagnostics, and formal inference. Data types include point patterns, line segment patterns, spatial windows, pixel images, tessellations, and linear networks. Exploratory methods include quadrat counts, K-functions and their simulation envelopes, nearest neighbour distance and empty space statistics, Fry plots, pair correlation function, kernel smoothed intensity, relative risk estimation with cross-validated bandwidth selection, mark correlatio [...truncated...]
Author: Adrian Baddeley [aut, cre] , Rolf Turner [aut] , Ege Rubak [aut]
Maintainer: Adrian Baddeley <Adrian.Baddeley@curtin.edu.au>

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Package pooledpeaks updated to version 1.0.7 with previous version 1.0.6 dated 2024-09-12

Title: Genetic Analysis of Pooled Samples
Description: Analyzing genetic data obtained from pooled samples. This package can read in Fragment Analysis output files, process the data, and score peaks, as well as facilitate various analyses, including cluster analysis, calculation of genetic distances and diversity indices, as well as bootstrap resampling for statistical inference. Specifically tailored to handle genetic data efficiently, researchers can explore population structure, genetic differentiation, and genetic relatedness among samples. We updated some functions from Covarrubias-Pazaran et al. (2016) <doi:10.1186/s12863-016-0365-6> to allow for the use of new file formats and referenced the following to write our genetic analysis functions: Long et al. (2022) <doi:10.1038/s41598-022-04776-0>, Jost (2008) <doi:10.1111/j.1365-294x.2008.03887.x>, Nei (1973) <doi:10.1073/pnas.70.12.3321>, Foulley et al. (2006) <doi:10.1016/j.livprodsci.2005.10.021>, Chao et al. (2008) <doi:10.1111/j.1541-0420.2008.01010 [...truncated...]
Author: Kathleen Kuesters [aut, cre, cph] , Jeffrey Long [aut], Jessica Blanton [aut], Walter Blank [ctb], Jeffrey Kovach [ctb], Ronald Blanton [ctb]
Maintainer: Kathleen Kuesters <kathleen.kuesters@gmail.com>

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Package hdar updated to version 1.0.4 with previous version 1.0.2 dated 2024-09-28

Title: 'REST' API Client for Accessing Data on 'WEkEO HDA V2'
Description: Provides seamless access to the WEkEO Harmonised Data Access (HDA) API, enabling users to query, download, and process data efficiently from the HDA platform. With 'hdar', researchers and data scientists can integrate the extensive HDA datasets into their R workflows, enhancing their data analysis capabilities. Comprehensive information on the API functionality and usage is available at <https://gateway.prod.wekeo2.eu/hda-broker/docs>.
Author: Matteo Mattiuzzi [aut, cre]
Maintainer: Matteo Mattiuzzi <matteo.mattiuzzi@eea.europa.eu>

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Package vivainsights updated to version 0.5.5 with previous version 0.5.4 dated 2024-09-06

Title: Analyze and Visualize Data from 'Microsoft Viva Insights'
Description: Provides a versatile range of functions, including exploratory data analysis, time-series analysis, organizational network analysis, and data validation, whilst at the same time implements a set of best practices in analyzing and visualizing data specific to 'Microsoft Viva Insights'.
Author: Martin Chan [aut, cre], Carlos Morales [aut]
Maintainer: Martin Chan <martin.chan@microsoft.com>

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Package RRBoost updated to version 0.2 with previous version 0.1 dated 2020-10-13

Title: A Robust Boosting Algorithm
Description: An implementation of robust boosting algorithms for regression in R. This includes the RRBoost method proposed in the paper "Robust Boosting for Regression Problems" (Ju X and Salibian-Barrera M. 2020) <doi:10.1016/j.csda.2020.107065>. It also implements previously proposed boosting algorithms in the simulation section of the paper: L2Boost, LADBoost, MBoost (Friedman, J. H. (2001) <doi:10.1214/aos/1013203451>) and Robloss (Lutz et al. (2008) <doi:10.1016/j.csda.2007.11.006>).
Author: Xiaomeng Ju [aut, cre], Matias Salibian-Barrera [aut]
Maintainer: Xiaomeng Ju <xiaomeng.ju@stat.ubc.ca>

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Package polylabelr updated to version 0.3.0 with previous version 0.2.0 dated 2020-04-19

Title: Find the Pole of Inaccessibility (Visual Center) of a Polygon
Description: A wrapper around the C++ library 'polylabel' from 'Mapbox', providing an efficient routine for finding the approximate pole of inaccessibility of a polygon, which usually serves as an excellent candidate for labeling of a polygon.
Author: Johan Larsson [aut, cre] , Kent Johnson [ctb], Mapbox [cph]
Maintainer: Johan Larsson <johanlarsson@outlook.com>

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Package HelpersMG updated to version 6.3 with previous version 6.2 dated 2024-08-23

Title: Tools for Environmental Analyses, Ecotoxicology and Various R Functions
Description: Contains miscellaneous functions useful for managing 'NetCDF' files (see <https://en.wikipedia.org/wiki/NetCDF>), get moon phase and time for sun rise and fall, tide level, analyse and reconstruct periodic time series of temperature with irregular sinusoidal pattern, show scales and wind rose in plot with change of color of text, Metropolis-Hastings algorithm for Bayesian MCMC analysis, plot graphs or boxplot with error bars, search files in disk by there names or their content, read the contents of all files from a folder at one time.
Author: Marc Girondot [aut, cre]
Maintainer: Marc Girondot <marc.girondot@gmail.com>

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Package eoa3 updated to version 1.0.0.2 with previous version 1.0.0.1 dated 2023-07-04

Title: Wildlife Mortality Estimator for Low Fatality Rates and Imperfect Detection
Description: Evidence of Absence software (EoA) is a user-friendly application for estimating bird and bat fatalities at wind farms and designing search protocols. The software is particularly useful in addressing whether the number of fatalities has exceeded a given threshold and what search parameters are needed to give assurance that thresholds were not exceeded. The models are applicable even when zero carcasses have been found in searches, following Huso et al. (2015) <doi:10.1890/14-0764.1>, Dalthorp et al. (2017) <doi:10.3133/ds1055>, and Dalthorp and Huso (2015) <doi:10.3133/ofr20151227>.
Author: Daniel Dalthorp [aut, cre]
Maintainer: Daniel Dalthorp <ddalthorp@protonmail.com>

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Package datacutr updated to version 0.2.0 with previous version 0.1.0 dated 2023-03-31

Title: SDTM Datacut
Description: Supports the process of applying a cut to Standard Data Tabulation Model (SDTM), as part of the analysis of specific points in time of the data, normally as part of investigation into clinical trials. The functions support different approaches of cutting to the different domains of SDTM normally observed.
Author: Tim Barnett [cph, aut, cre], Nathan Rees [aut], Alana Harris [aut], Cara Andrews [aut]
Maintainer: Tim Barnett <timothy.barnett@roche.com>

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Package watson updated to version 0.5 with previous version 0.4 dated 2023-06-01

Title: Fitting and Simulating Mixtures of Watson Distributions
Description: Tools for fitting and simulating mixtures of Watson distributions. The random sampling scheme of the package offers two sampling algorithms that are based of the results of Sablica, Hornik and Leydold (2022) <https://research.wu.ac.at/en/publications/random-sampling-from-the-watson-distribution>. What is more, the package offers a smart tool to combine these two methods, and based on the selected parameters, it approximates the relative sampling speed for both methods and picks the faster one. In addition, the package offers a fitting function for the mixtures of Watson distribution, that uses the expectation-maximization (EM) algorithm. Special features are the possibility to use multiple variants of the E-step and M-step, sparse matrices for the data representation and state of the art methods for numerical evaluation of needed special functions using the results of Sablica and Hornik (2022) <https://www.ams.org/journals/mcom/2022-91-334/S0025-5718-2021-03690-X/>.
Author: Lukas Sablica [aut, cre] , Kurt Hornik [aut] , Josef Leydold [aut] , Gerard Jungman [ctb, cph] , Brian Gough [ctb, cph]
Maintainer: Lukas Sablica <lsablica@wu.ac.at>

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Package hyperbolicDEA updated to version 1.0.1 with previous version 1.0.0 dated 2024-03-18

Title: Hyperbolic DEA Estimation
Description: Implements Data Envelopment Analysis (DEA) with a hyperbolic orientation using a non-linear programming solver. It enables flexible estimations with weight restrictions, non-discretionary variables, and a generalized distance function. Additionally, it allows for the calculation of slacks and super-efficiency scores. The methods are detailed in Öttl et al. (2023), <doi:10.1016/j.dajour.2023.100343>. Furthermore, the package provides a non-linear profitability estimation built upon the DEA framework.
Author: Alexander Oettl [cre, aut] , Daniel Gulde [aut]
Maintainer: Alexander Oettl <alexoettl34@gmail.com>

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Package cols updated to version 1.3 with previous version 1.2 dated 2024-10-16

Title: Constrained Ordinary Least Squares
Description: Constrained ordinary least squares is performed. One constraint is that all beta coefficients (including the constant) cannot be negative. They can be either 0 or strictly positive. Another constraint is that the sum of the beta coefficients equals a constant. References: Hansen, B. E. (2022). Econometrics, Princeton University Press. <ISBN:9780691235899>.
Author: Michail Tsagris [aut, cre]
Maintainer: Michail Tsagris <mtsagris@uoc.gr>

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Package CDsampling updated to version 0.1.2 with previous version 0.1.1 dated 2024-10-13

Title: 'CDsampling': Constraint Sampling in Paid Research Studies
Description: In the context of paid research studies and clinical trials, budget considerations and patient sampling from available populations are subject to inherent constraints. We introduce the 'CDsampling' package, which integrates optimal design theories within the framework of constrained sampling. This package offers the possibility to find both D-optimal approximate and exact allocations for samplings with or without constraints. Additionally, it provides functions to find constrained uniform sampling as a robust sampling strategy with limited model information. Our package offers functions for the computation of the Fisher information matrix under generalized linear models (including regular linear regression model) and multinomial logistic models.To demonstrate the applications, we also provide a simulated dataset and a real dataset embedded in the package. Yifei Huang, Liping Tong, and Jie Yang (2025)<doi:10.5705/ss.202022.0414>.
Author: Yifei Huang [aut, cre], Liping Tong [aut], Jie Yang [aut]
Maintainer: Yifei Huang <yhuan39@uic.edu>

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Package LikertMakeR updated to version 0.4.0 with previous version 0.3.0 dated 2024-05-19

Title: Synthesise and Correlate Likert Scale and Related Rating-Scale Data
Description: Synthesise Likert scale and related rating-scale data with predefined first and second moments (mean and standard deviation), and, optionally, correlate multiple vectors using a predefined correlation matrix. Additionally, generate synthetic rating-scale items with a predefined Cronbach's Alpha, or create rating-scale items based on a predefined summated scale.
Author: Hume Winzar [cre, aut]
Maintainer: Hume Winzar <winzar@gmail.com>

Diff between LikertMakeR versions 0.3.0 dated 2024-05-19 and 0.4.0 dated 2024-11-19

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More information about LikertMakeR at CRAN
Permanent link

Package kergp updated to version 0.5.8 with previous version 0.5.7 dated 2024-02-05

Title: Gaussian Process Laboratory
Description: Gaussian process regression with an emphasis on kernels. Quantitative and qualitative inputs are accepted. Some pre-defined kernels are available, such as radial or tensor-sum for quantitative inputs, and compound symmetry, low rank, group kernel for qualitative inputs. The user can define new kernels and composite kernels through a formula mechanism. Useful methods include parameter estimation by maximum likelihood, simulation, prediction and leave-one-out validation.
Author: Yves Deville [aut] , David Ginsbourger [aut] , Olivier Roustant [aut, cre], Nicolas Durrande [ctb]
Maintainer: Olivier Roustant <roustant@insa-toulouse.fr>

Diff between kergp versions 0.5.7 dated 2024-02-05 and 0.5.8 dated 2024-11-19

 DESCRIPTION              |   24 ++++++++++++++++++------
 MD5                      |   18 +++++++++---------
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More information about kergp at CRAN
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Package HMMRel updated to version 0.1.1 with previous version 0.1.0 dated 2024-11-15

Title: Hidden Markov Models for Reliability and Maintenance
Description: Reliability Analysis and Maintenance Optimization using Hidden Markov Models (HMM). The use of HMMs to model the state of a system which is not directly observable and instead certain indicators (signals) of the true situation are provided via a control system. A hidden model can provide key information about the system dependability, such as the reliability of the system and related measures. An estimation procedure is implemented based on the Baum-Welch algorithm. Classical structures such as K-out-of-N systems and Shock models are illustrated. Finally, the maintenance of the system is considered in the HMM context and two functions for new preventive maintenance strategies are considered. Maintenance efficiency is measured in terms of expected cost. Methods are described in Gamiz, Limnios, and Segovia-Garcia (2023) <doi:10.1016/j.ejor.2022.05.006>.
Author: M.L. Gamiz [aut, cre, cph], N. Limnios [aut, cph], M.C. Segovia-Garcia [aut, cph]
Maintainer: M.L. Gamiz <mgamiz@ugr.es>

Diff between HMMRel versions 0.1.0 dated 2024-11-15 and 0.1.1 dated 2024-11-19

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More information about HMMRel at CRAN
Permanent link

Package ggiraph updated to version 0.8.11 with previous version 0.8.10 dated 2024-05-17

Title: Make 'ggplot2' Graphics Interactive
Description: Create interactive 'ggplot2' graphics using 'htmlwidgets'.
Author: David Gohel [aut, cre], Panagiotis Skintzos [aut], Mike Bostock [cph] , Speros Kokenes [cph] , Eric Shull [cph] , Lee Thomason [cph] , Vladimir Agafonkin [cph] , Eric Book [ctb]
Maintainer: David Gohel <david.gohel@ardata.fr>

Diff between ggiraph versions 0.8.10 dated 2024-05-17 and 0.8.11 dated 2024-11-19

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More information about ggiraph at CRAN
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Package file2meco updated to version 0.9.1 with previous version 0.9.0 dated 2024-10-31

Title: Transform Files to 'microtable' Object with 'microeco' Package
Description: Transform output files of some tools to the 'microtable' object of 'microtable' class in 'microeco' package. The 'microtable' class is the basic class in 'microeco' package and is necessary for the downstream microbial community data analysis.
Author: Chi Liu [aut, cre]
Maintainer: Chi Liu <liuchi0426@126.com>

Diff between file2meco versions 0.9.0 dated 2024-10-31 and 0.9.1 dated 2024-11-19

 DESCRIPTION    |    6 +++---
 MD5            |    4 ++--
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Package tram updated to version 1.2-0 with previous version 1.1-2 dated 2024-10-04

Title: Transformation Models
Description: Formula-based user-interfaces to specific transformation models implemented in package 'mlt' (<DOI:10.32614/CRAN.package.mlt>, <DOI:10.32614/CRAN.package.mlt.docreg>). 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>

Diff between tram versions 1.1-2 dated 2024-10-04 and 1.2-0 dated 2024-11-19

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More information about tram at CRAN
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New package pseudobibeR with initial version 1.2
Package: pseudobibeR
Title: Aggregate Counts of Linguistic Features
Version: 1.2
Date: 2024-11-18
Description: Calculates the lexicogrammatical and functional features described by Biber (1985) <doi:10.1515/ling.1985.23.2.337> and widely used for text-type, register, and genre classification tasks.
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: TRUE
Depends: R (>= 3.5.0)
Imports: dplyr, purrr, quanteda, quanteda.textstats, rlang, stringr, tibble, magrittr
Suggests: testthat (>= 3.0.0), udpipe
NeedsCompilation: no
Packaged: 2024-11-18 19:20:40 UTC; alexreinhart
Author: David Brown [aut, cre] , Alex Reinhart [aut]
Maintainer: David Brown <dwb2@andrew.cmu.edu>
Repository: CRAN
Date/Publication: 2024-11-19 12:20:06 UTC

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New package mvvg with initial version 0.1.0
Package: mvvg
Title: Matrix-Variate Variance-Gamma Distribution
Version: 0.1.0
Description: Rudimentary functions for sampling and calculating density from the matrix-variate variance-gamma distribution.
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
Imports: MixMatrix, nlme, psych
Suggests: knitr, rmarkdown
NeedsCompilation: no
Packaged: 2024-11-18 20:58:53 UTC; soonsk
Author: Samuel Soon [aut, cre]
Maintainer: Samuel Soon <samksoon2@gmail.com>
Depends: R (>= 3.5.0)
Repository: CRAN
Date/Publication: 2024-11-19 12:20:27 UTC

More information about mvvg at CRAN
Permanent link

New package LFM with initial version 0.1.0
Package: LFM
Title: Laplace Factor Model Analysis and Evaluation
Date: 2024-11-18
Version: 0.1.0
Description: Enables the generation of Laplace factor models across diverse Laplace distributions and facilitates the application of Sparse Online Principal Component (SOPC), Incremental Principal Component (IPC), Parallel Principal Component (PPC), Sparse Approximate Principal Component (SAPC), Standard Principal Component (SPC), and Farm Test methods to these models. Evaluates the efficacy of these methods within the context of Laplace factor models by scrutinizing parameter estimation accuracy, mean square error, and the degree of sparsity.
License: MIT + file LICENSE
Encoding: UTF-8
Imports: stats, FarmTest, MASS, SOPC, LaplacesDemon, matrixcalc, relliptical
NeedsCompilation: no
Language: en-US
Author: Guangbao Guo [aut, cre], Siqi Liu [aut]
Maintainer: Guangbao Guo <ggb11111111@163.com>
Depends: R (>= 3.5.0)
BuildManual: yes
Suggests: testthat (>= 3.0.0)
Packaged: 2024-11-18 10:54:04 UTC; R7000
Repository: CRAN
Date/Publication: 2024-11-19 12:30:09 UTC

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New package GRIN2 with initial version 1.0
Package: GRIN2
Title: Genomic Random Interval (GRIN)
Version: 1.0
Description: Improved version of 'GRIN' software that streamlines its use in practice to analyze genomic lesion data, accelerate its computing, and expand its analysis capabilities to answer additional scientific questions including a rigorous evaluation of the association of genomic lesions with RNA expression. Pounds, Stan, et al. (2013) <DOI:10.1093/bioinformatics/btt372>.
License: GPL (>= 3)
Encoding: UTF-8
Imports: biomaRt, circlize, ComplexHeatmap, data.table, dplyr, EnsDb.Hsapiens.v75, ensembldb, forcats, GenomeInfoDb, ggplot2, graphics, grDevices, grid, gridGraphics, Gviz, magrittr, stats, stringr, survival, tibble, tidyselect, utils, writexl
Suggests: knitr, rmarkdown
NeedsCompilation: no
Maintainer: Abdelrahman Elsayed <aelsayed@stjude.org>
Depends: R (>= 4.2.0)
LazyData: true
VignetteBuilder: knitr
URL: https://github.com/abdel-elsayed87/GRIN2
BugReports: https://github.com/abdel-elsayed87/GRIN2/issues
Packaged: 2024-11-18 22:39:09 UTC; aelsa
Author: Abdelrahman Elsayed [aut, cre, cph] , Xueyuan Cao [aut], Lakshmi Anuhya patibandla [aut], Stanley Pounds [aut, cph]
Repository: CRAN
Date/Publication: 2024-11-19 12:30:36 UTC

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New package forestdynR with initial version 0.0.1
Package: forestdynR
Title: Calculate Forest Dynamics
Version: 0.0.1
Maintainer: Pedro Higuchi <higuchip@gmail.com>
Description: Determines the dynamics of tree species communities (mortality rates, recruitment, loss and gain in basal area, net changes and turnover). Important notes are a) The 'forest_df' argument (data) must contain the columns 'plot' (plot identification), 'spp' (species identification), DBH_1 (Diameter at breast height in first year of measure) and DBH_2 (Diameter at breast height in second year of measure). DBH_1 and DBH_2 must be numeric values; b) example input file in 'data(forest_df_example)'; c) The argument 'inv_time' represents the time between inventories, in years; d) The 'coord' argument must be of the type 'c(longitude, latitude)', with decimal degree values; e) Argument 'add_wd' represents a dataframe with wood density values (g cm-3) format with three columns ('genus', 'species', 'wd'). This argument is set to NULL by default, and if isn't provided, the wood density will be estimated with the getWoodDensity() function from the 'BIOMASS' package.
License: GPL (>= 2)
URL: https://github.com/higuchip/forestdynR
BugReports: https://github.com/higuchip/forestdynR/issues
Depends: R (>= 4.3.0)
Imports: BIOMASS (>= 2.1.11), tcltk (>= 1.0.0),
Suggests: covr, knitr, rmarkdown, spelling, testthat (>= 3.0.0)
VignetteBuilder: knitr
Encoding: UTF-8
Language: en-US
LazyData: true
NeedsCompilation: no
Packaged: 2024-11-18 20:37:29 UTC; optimus-prime
Author: Pedro Higuchi [cre, aut], Ana Carolina Silva [aut], Adam Slabadack [aut]
Repository: CRAN
Date/Publication: 2024-11-19 12:20:41 UTC

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New package talkr with initial version 0.1.3
Package: talkr
Title: Plotting Conversation Data
Version: 0.1.3
Description: Visualisation, analysis and quality control of conversational data. Rapid and visual insights into the nature, timing and quality of time-aligned annotations in conversational corpora. For more details, see Dingemanse et al., (2022) <doi:10.18653/v1/2022.acl-long.385>.
License: Apache License (>= 2)
Encoding: UTF-8
VignetteBuilder: knitr
Depends: R (>= 3.5.0)
Imports: cowplot, dplyr, ggplot2, ggthemes, knitr, stats, stringr, tidyr, tidyselect
Suggests: rmarkdown, testthat (>= 3.0.0), pkgdown, ggrepel, utils
NeedsCompilation: no
Packaged: 2024-11-15 13:53:36 UTC; pablo
Author: Mark Dingemanse [aut, cre], Barbara Vreede [aut], Eva Viviani [aut], Pablo Rodriguez-Sanchez [aut], Andreas Liesenfeld [ctb], Netherlands eScience Center [cph, fnd]
Maintainer: Mark Dingemanse <mark.dingemanse@ru.nl>
Repository: CRAN
Date/Publication: 2024-11-19 11:50:03 UTC

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Package schoRsch updated to version 1.11 with previous version 1.10 dated 2022-11-01

Title: Tools for Analyzing Factorial Experiments
Description: Offers a helping hand to psychologists and other behavioral scientists who routinely deal with experimental data from factorial experiments. It includes several functions to format output from other R functions according to the style guidelines of the APA (American Psychological Association). This formatted output can be copied directly into manuscripts to facilitate data reporting. These features are backed up by a toolkit of several small helper functions, e.g., offering out-of-the-box outlier removal. The package lends its name to Georg "Schorsch" Schuessler, ingenious technician at the Department of Psychology III, University of Wuerzburg. For details on the implemented methods, see Roland Pfister and Markus Janczyk (2016) <doi: 10.20982/tqmp.12.2.p147>.
Author: Roland Pfister [aut, cre], Markus Janczyk [aut]
Maintainer: Roland Pfister <mail@roland-pfister.net>

Diff between schoRsch versions 1.10 dated 2022-11-01 and 1.11 dated 2024-11-19

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Package mlt.docreg updated to version 1.1-10 with previous version 1.1-9 dated 2024-09-20

Title: Most Likely Transformations: Documentation and Regression Tests
Description: Additional documentation, a package vignette and regression tests for package mlt.
Author: Torsten Hothorn [aut, cre]
Maintainer: Torsten Hothorn <Torsten.Hothorn@R-project.org>

Diff between mlt.docreg versions 1.1-9 dated 2024-09-20 and 1.1-10 dated 2024-11-19

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New package ecdata with initial version 1.1.1
Package: ecdata
Title: Loads Data from the Executive Communications Dataset
Version: 1.1.1
Description: A minimal package for downloading data from 'GitHub' repositories of the Executive Communications Database.
License: CC BY 4.0
Encoding: UTF-8
LazyData: true
URL: https://github.com/Executive-Communications-Dataset/ecdata,https://executive-communications-dataset.github.io/ecdata/
BugReports: https://github.com/Executive-Communications-Dataset/ecdata/issues
Depends: R (>= 4.0)
Imports: arrow (>= 16.1.0), cli (>= 3.6.3), rlang (>= 1.1.0), glue (>= 1.4.0), piggyback (>= 0.1.5), utils, tools, cachem (>= 1.0.0), memoise (>= 2.0.0), vctrs, curl
Suggests: duckplyr, testthat (>= 3.0.0), data.table, dplyr, altdoc, knitr, rmarkdown
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2024-11-18 18:12:34 UTC; josh
Author: Joshua Allen [aut, cre, cph] , Ryan Carlin [ctb], Juan Gomez-Gomez-Cruces [ctb], Will Horne [aut, ctb], Jamie Lindh [ctb], Cecilia Martinez-Gallardo [ctb], Miles Massesy [ctb]
Maintainer: Joshua Allen <joshua.f.allen@gmail.com>
Repository: CRAN
Date/Publication: 2024-11-19 12:00:10 UTC

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New package CSTE with initial version 3.0.0
Package: CSTE
Version: 3.0.0
Date: 2024-11-16
Title: Covariate Specific Treatment Effect (CSTE) Curve
Description: A uniform statistical inferential tool in making individualized treatment decisions, which implements the methods of Ma et al. (2017)<DOI:10.1177/0962280214541724> and Guo et al. (2021)<DOI:10.1080/01621459.2020.1865167>. It uses a flexible semiparametric modeling strategy for heterogeneous treatment effect estimation in high-dimensional settings and can gave valid confidence bands. Based on it, one can find the subgroups of patients that benefit from each treatment, thereby making individualized treatment selection.
License: GPL (>= 2)
Encoding: UTF-8
Imports: Rcpp (>= 1.0.4), fda, splines, survival, locpol, dfoptim
LinkingTo: Rcpp
Suggests: mvtnorm, sigmoid
NeedsCompilation: yes
Packaged: 2024-11-18 16:47:21 UTC; wenjiehu
Author: Peng Wu [aut], Wenjie Hu [aut, cre], Yuhao Deng [aut], Haoxiang Wang [aut], Xiaohua Zhou [aut]
Maintainer: Wenjie Hu <huwenjie@pku.edu.cn>
Repository: CRAN
Date/Publication: 2024-11-19 12:00:15 UTC

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Package spatstat.linnet updated to version 3.2-3 with previous version 3.2-2 dated 2024-09-20

Title: Linear Networks Functionality of the 'spatstat' Family
Description: Defines types of spatial data on a linear network and provides functionality for geometrical operations, data analysis and modelling of data on a linear network, in the 'spatstat' family of packages. Contains definitions and support for linear networks, including creation of networks, geometrical measurements, topological connectivity, geometrical operations such as inserting and deleting vertices, intersecting a network with another object, and interactive editing of networks. Data types defined on a network include point patterns, pixel images, functions, and tessellations. Exploratory methods include kernel estimation of intensity on a network, K-functions and pair correlation functions on a network, simulation envelopes, nearest neighbour distance and empty space distance, relative risk estimation with cross-validated bandwidth selection. Formal hypothesis tests of random pattern (chi-squared, Kolmogorov-Smirnov, Monte Carlo, Diggle-Cressie-Loosmore-Ford, Dao-Genton, two-stage Mont [...truncated...]
Author: Adrian Baddeley [aut, cre, cph] , Rolf Turner [aut, cph] , Ege Rubak [aut, cph] , Greg McSwiggan [aut, cph], Tilman Davies [ctb, cph], Mehdi Moradi [ctb, cph], Suman Rakshit [ctb, cph], Ottmar Cronie [ctb]
Maintainer: Adrian Baddeley <Adrian.Baddeley@curtin.edu.au>

Diff between spatstat.linnet versions 3.2-2 dated 2024-09-20 and 3.2-3 dated 2024-11-19

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Package openairmaps updated to version 0.9.1 with previous version 0.9.0 dated 2024-05-19

Title: Create Maps of Air Pollution Data
Description: Combine the air quality data analysis methods of 'openair' with the JavaScript 'Leaflet' (<https://leafletjs.com/>) library. Functionality includes plotting site maps, "directional analysis" figures such as polar plots, and air mass trajectories.
Author: Jack Davison [cre, aut] , David Carslaw [aut]
Maintainer: Jack Davison <jack.davison@ricardo.com>

Diff between openairmaps versions 0.9.0 dated 2024-05-19 and 0.9.1 dated 2024-11-19

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Package mulea updated to version 1.1.1 with previous version 1.1.0 dated 2024-09-24

Title: Enrichment Analysis Using Multiple Ontologies and False Discovery Rate
Description: Background - Traditional gene set enrichment analyses are typically limited to a few ontologies and do not account for the interdependence of gene sets or terms, resulting in overcorrected p-values. To address these challenges, we introduce mulea, an R package offering comprehensive overrepresentation and functional enrichment analysis. Results - mulea employs a progressive empirical false discovery rate (eFDR) method, specifically designed for interconnected biological data, to accurately identify significant terms within diverse ontologies. mulea expands beyond traditional tools by incorporating a wide range of ontologies, encompassing Gene Ontology, pathways, regulatory elements, genomic locations, and protein domains. This flexibility enables researchers to tailor enrichment analysis to their specific questions, such as identifying enriched transcriptional regulators in gene expression data or overrepresented protein domains in protein sets. To facilitate seamless analysis, mulea p [...truncated...]
Author: Cezary Turek [aut] , Marton Olbei [aut] , Tamas Stirling [aut, cre] , Gergely Fekete [aut] , Ervin Tasnadi [aut] , Leila Gul [aut], Balazs Bohar [aut] , Balazs Papp [aut] , Wiktor Jurkowski [aut] , Eszter Ari [aut, cph]
Maintainer: Tamas Stirling <stirling.tamas@gmail.com>

Diff between mulea versions 1.1.0 dated 2024-09-24 and 1.1.1 dated 2024-11-19

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Package cleaner updated to version 1.5.5 with previous version 1.5.4 dated 2022-10-29

Title: Fast and Easy Data Cleaning
Description: Data cleaning functions for classes logical, factor, numeric, character, currency and Date to make data cleaning fast and easy. Relying on very few dependencies, it provides smart guessing, but with user options to override anything if needed.
Author: Matthijs S. Berends [aut, cre]
Maintainer: Matthijs S. Berends <m.s.berends@umcg.nl>

Diff between cleaner versions 1.5.4 dated 2022-10-29 and 1.5.5 dated 2024-11-19

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New package where with initial version 1.0.0
Package: where
Title: Vectorised Substitution and Evaluation
Version: 1.0.0
Description: Provides a clean syntax for vectorising the use of Non-Standard Evaluation (NSE), for example in 'ggplot2', 'dplyr', or 'data.table'.
License: MIT + file LICENSE
URL: https://github.com/KiwiMateo/where
BugReports: https://github.com/KiwiMateo/where/issues
Suggests: data.table, dplyr, ggplot2, knitr, rmarkdown, testthat (>= 3.0.0)
VignetteBuilder: knitr
Encoding: UTF-8
NeedsCompilation: no
Packaged: 2024-11-18 06:45:14 UTC; OEM
Author: Matt Hendtlass [aut, cre]
Maintainer: Matt Hendtlass <m.hendtlass@gmail.com>
Repository: CRAN
Date/Publication: 2024-11-19 09:40:02 UTC

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Package spatstat.model updated to version 3.3-3 with previous version 3.3-2 dated 2024-09-19

Title: Parametric Statistical Modelling and Inference for the 'spatstat' Family
Description: Functionality for parametric statistical modelling and inference for spatial data, mainly spatial point patterns, in the 'spatstat' family of packages. (Excludes analysis of spatial data on a linear network, which is covered by the separate package 'spatstat.linnet'.) Supports parametric modelling, formal statistical inference, and model validation. Parametric models include Poisson point processes, Cox point processes, Neyman-Scott cluster processes, Gibbs point processes and determinantal point processes. Models can be fitted to data using maximum likelihood, maximum pseudolikelihood, maximum composite likelihood and the method of minimum contrast. Fitted models can be simulated and predicted. Formal inference includes hypothesis tests (quadrat counting tests, Cressie-Read tests, Clark-Evans test, Berman test, Diggle-Cressie-Loosmore-Ford test, scan test, studentised permutation test, segregation test, ANOVA tests of fitted models, adjusted composite likelihood ratio test, envelope t [...truncated...]
Author: Adrian Baddeley [aut, cre, cph] , Rolf Turner [aut, cph] , Ege Rubak [aut, cph] , Kasper Klitgaard Berthelsen [ctb], Achmad Choiruddin [ctb, cph], Jean-Francois Coeurjolly [ctb], Ottmar Cronie [ctb], Tilman Davies [ctb], Julian Gilbey [ctb], Yongtao [...truncated...]
Maintainer: Adrian Baddeley <Adrian.Baddeley@curtin.edu.au>

Diff between spatstat.model versions 3.3-2 dated 2024-09-19 and 3.3-3 dated 2024-11-19

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 10 files changed, 91 insertions(+), 45 deletions(-)

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New package OutSeekR with initial version 1.0.0
Package: OutSeekR
Title: Statistical Approach to Outlier Detection in RNA-Seq and Related Data
Version: 1.0.0
Date: 2024-11-15
Description: An approach to outlier detection in RNA-seq and related data based on five statistics. 'OutSeekR' implements an outlier test by comparing the distributions of these statistics in observed data with those of simulated null data.
Depends: R (>= 2.10)
Imports: future.apply, gamlss, gamlss.dist, lsa, truncnorm
Suggests: future, knitr, rmarkdown, testthat (>= 3.0.0)
License: GPL-2
Encoding: UTF-8
LazyData: true
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2024-11-15 23:56:34 UTC; danknight
Author: Jee Yun Han [aut], John Sahrmann [aut], Jaron Arbet [ctb], Paul Boutros [aut, cre, cph]
Maintainer: Paul Boutros <pboutros@mednet.ucla.edu>
Repository: CRAN
Date/Publication: 2024-11-19 09:10:05 UTC

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New package multiDoE with initial version 0.9.2
Package: multiDoE
Title: Multi-Criteria Design of Experiments for Optimal Design
Version: 0.9.2
Maintainer: Andrea Melloncelli <andrea.melloncelli@vanlog.it>
Description: Multi-criteria design of experiments algorithm that simultaneously optimizes up to six different criteria ('I', 'Id', 'D', 'Ds', 'A' and 'As'). The algorithm finds the optimal Pareto front and, if requested, selects a possible symmetrical design on it. The symmetrical design is selected based on two techniques: minimum distance with the Utopia point or the 'TOPSIS' approach.
License: CC BY 4.0
URL: https://github.com/andreamelloncelli/multiDoE
Imports: ggplot2, magrittr, plotly, pracma
Suggests: devtools, here, knitr, logr, markdown, rgl, rmarkdown, testthat (>= 3.0.0), usethis
VignetteBuilder: knitr
Encoding: UTF-8
NeedsCompilation: no
Packaged: 2024-11-18 08:46:59 UTC; daco
Author: Francesca Cucchi [aut], Andrea Melloncelli [aut, cre], Francesco Sambo [aut], Kalliopi Mylona [aut], Matteo Borrotti [aut]
Depends: R (>= 3.5.0)
Repository: CRAN
Date/Publication: 2024-11-19 09:50:02 UTC

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Package LST updated to version 2.0.0 with previous version 1.1.0 dated 2021-05-17

Title: Land Surface Temperature Retrieval for Landsat 8
Description: Calculates Land Surface Temperature from Landsat band 10 and 11. Revision of the Single-Channel Algorithm for Land Surface Temperature Retrieval From Landsat Thermal-Infrared Data. Jimenez-Munoz JC, Cristobal J, Sobrino JA, et al (2009). <doi: 10.1109/TGRS.2008.2007125>. Land surface temperature retrieval from LANDSAT TM 5. Sobrino JA, Jiménez-Muñoz JC, Paolini L (2004). <doi:10.1016/j.rse.2004.02.003>. Surface temperature estimation in Singhbhum Shear Zone of India using Landsat-7 ETM+ thermal infrared data. Srivastava PK, Majumdar TJ, Bhattacharya AK (2009). <doi: 10.1016/j.asr.2009.01.023>. Mapping land surface emissivity from NDVI: Application to European, African, and South American areas. Valor E (1996). <doi:10.1016/0034-4257(96)00039-9>. On the relationship between thermal emissivity and the normalized difference vegetation index for natural surfaces. Van de Griend AA, Owe M (1993). <doi:10.1080/01431169308904400>. Land Surface Temperature Retrieva [...truncated...]
Author: Bappa Das [aut, cre] , Debasish Roy [aut, ctb], Debashis Chakraborty [aut, ctb], Pooja Rathore [aut, ctb]
Maintainer: Bappa Das <bappa.iari.1989@gmail.com>

Diff between LST versions 1.1.0 dated 2021-05-17 and 2.0.0 dated 2024-11-19

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New package deident with initial version 1.0.0
Package: deident
Title: Persistent Data Anonymization Pipeline
Version: 1.0.0
Description: A framework for the replicable removal of personally identifiable data (PID) in data sets. The package implements a suite of methods to suit different data types based on the suggestions of Garfinkel (2015) <doi:10.6028/NIST.IR.8053> and the ICO "Guidelines on Anonymization" (2012) <https://ico.org.uk/media/1061/anonymisation-code.pdf>.
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
Suggests: testthat (>= 3.0.0), checkmate, knitr, rmarkdown, roxygen2
Imports: R6, dplyr, openssl, tidyselect, rlang (>= 0.4.11), glue, purrr, stringr, yaml, readr, openxlsx, lemon, withr, fs
Depends: R (>= 2.10)
VignetteBuilder: knitr
Language: en-GB
NeedsCompilation: no
Packaged: 2024-11-18 11:36:38 UTC; rzc1
Author: Robert Cook [aut, cre] , Md Assaduzaman [aut] , Sarahjane Jones [aut]
Maintainer: Robert Cook <robert.cook@staffs.ac.uk>
Repository: CRAN
Date/Publication: 2024-11-19 09:50:06 UTC

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Package sgapi (with last version 1.0.2) was removed from CRAN

Previous versions (as known to CRANberries) which should be available via the Archive link are:

2024-03-28 1.0.2
2024-03-20 1.0.1
2024-03-18 1.0.0

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Package algaeClassify (with last version 2.0.3) was removed from CRAN

Previous versions (as known to CRANberries) which should be available via the Archive link are:

2024-10-11 2.0.3

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Package MXM (with last version 1.5.5) was removed from CRAN

Previous versions (as known to CRANberries) which should be available via the Archive link are:

2022-08-25 1.5.5
2022-06-06 1.5.4
2021-09-21 1.5.2
2021-02-23 1.5.1
2021-01-08 1.5.0
2020-09-03 1.4.9
2020-07-26 1.4.8
2020-05-06 1.4.7
2020-04-05 1.4.6
2019-12-06 1.4.5

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Package metaumbrella (with last version 1.0.11) was removed from CRAN

Previous versions (as known to CRANberries) which should be available via the Archive link are:

2024-03-08 1.0.11
2024-01-25 1.0.10
2023-11-06 1.0.9
2023-09-14 1.0.8
2023-08-22 1.0.7
2023-07-01 1.0.6
2022-06-13 1.0.5
2022-06-09 1.0.4
2022-05-06 1.0.3

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Package pkgdepR updated to version 1.1.1 with previous version 1.1.0 dated 2024-11-18

Title: Statically Determine Function Dependencies Between Packages
Description: Statically determine and visualize the function dependencies within and across packages. This may be useful for managing function dependencies across a code base of multiple R packages.
Author: Ed Peyton [aut, cre]
Maintainer: Ed Peyton <edppeyton@gmail.com>

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Package opendataformat updated to version 2.0.0 with previous version 1.3.0 dated 2024-10-07

Title: Reading and Writing Open Data Format Files
Description: The Open Data Format (ODF) is a new, non-proprietary, multilingual, metadata enriched, and zip-compressed data format with metadata structured in the Data Documentation Initiative (DDI) Codebook standard. This package allows reading and writing of data files in the Open Data Format (ODF) in R, and displaying metadata in different languages. For further information on the Open Data Format, see <https://opendataformat.github.io/>.
Author: Tom Hartl [aut, cre] , Claudia Saalbach [ctb]
Maintainer: Tom Hartl <thartl@diw.de>

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Package epiR updated to version 2.0.77 with previous version 2.0.76 dated 2024-09-15

Title: Tools for the Analysis of Epidemiological Data
Description: Tools for the analysis of epidemiological and surveillance data. Contains functions for directly and indirectly adjusting measures of disease frequency, quantifying measures of association on the basis of single or multiple strata of count data presented in a contingency table, computation of confidence intervals around incidence risk and incidence rate estimates and sample size calculations for cross-sectional, case-control and cohort studies. Surveillance tools include functions to calculate an appropriate sample size for 1- and 2-stage representative freedom surveys, functions to estimate surveillance system sensitivity and functions to support scenario tree modelling analyses.
Author: Mark Stevenson [aut, cre] , Evan Sergeant [aut], Cord Heuer [ctb], Telmo Nunes [ctb], Cord Heuer [ctb], Jonathon Marshall [ctb], Javier Sanchez [ctb], Ron Thornton [ctb], Jeno Reiczigel [ctb], Jim Robison-Cox [ctb], Paola Sebastiani [ctb], Peter Soly [...truncated...]
Maintainer: Mark Stevenson <mark.stevenson1@unimelb.edu.au>

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Package EFAfactors updated to version 1.1.1 with previous version 1.1.0 dated 2024-09-29

Title: Determining the Number of Factors in Exploratory Factor Analysis
Description: Provides a collection of standard factor retention methods in Exploratory Factor Analysis (EFA), making it easier to determine the number of factors. Traditional methods such as the scree plot by Cattell (1966) <doi:10.1207/s15327906mbr0102_10>, Kaiser-Guttman Criterion (KGC) by Guttman (1954) <doi:10.1007/BF02289162> and Kaiser (1960) <doi:10.1177/001316446002000116>, and flexible Parallel Analysis (PA) by Horn (1965) <doi:10.1007/BF02289447> based on eigenvalues form PCA or EFA are readily available. This package also implements several newer methods, such as the Empirical Kaiser Criterion (EKC) by Braeken and van Assen (2017) <doi:10.1037/met0000074>, Comparison Data (CD) by Ruscio and Roche (2012) <doi:10.1037/a0025697>, and Hull method by Lorenzo-Seva et al. (2011) <doi:10.1080/00273171.2011.564527>, as well as some AI-based methods like Comparison Data Forest (CDF) by Goretzko and Ruscio (2024) <doi:10.3758/s13428-023-02122-4> and F [...truncated...]
Author: Haijiang Qin [aut, cre, cph], Lei Guo [aut, cph]
Maintainer: Haijiang Qin <haijiang133@outlook.com>

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Package cmstatr updated to version 0.10.0 with previous version 0.9.3 dated 2024-03-14

Title: Statistical Methods for Composite Material Data
Description: An implementation of the statistical methods commonly used for advanced composite materials in aerospace applications. This package focuses on calculating basis values (lower tolerance bounds) for material strength properties, as well as performing the associated diagnostic tests. This package provides functions for calculating basis values assuming several different distributions, as well as providing functions for non-parametric methods of computing basis values. Functions are also provided for testing the hypothesis that there is no difference between strength and modulus data from an alternate sample and that from a "qualification" or "baseline" sample. For a discussion of these statistical methods and their use, see the Composite Materials Handbook, Volume 1 (2012, ISBN: 978-0-7680-7811-4). Additional details about this package are available in the paper by Kloppenborg (2020, <doi:10.21105/joss.02265>).
Author: Stefan Kloppenborg [aut, cre] , Billy Cheng [ctb], Ally Fraser [ctb], Jeffrey Borlik [ctb], Brice Langston [ctb], Comtek Advanced Structures, Ltd. [fnd]
Maintainer: Stefan Kloppenborg <stefan@kloppenborg.ca>

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Package assertions updated to version 0.2.0 with previous version 0.1.0 dated 2023-06-02

Title: Simple Assertions for Beautiful and Customisable Error Messages
Description: Provides simple assertions with sensible defaults and customisable error messages. It offers convenient assertion call wrappers and a general assert function that can handle any condition. Default error messages are user friendly and easily customized with inline code evaluation and styling powered by the 'cli' package.
Author: Sam El-Kamand [aut, cre, cph]
Maintainer: Sam El-Kamand <sam.elkamand@gmail.com>

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Package rsconnect updated to version 1.3.3 with previous version 1.3.2 dated 2024-10-28

Title: Deploy Docs, Apps, and APIs to 'Posit Connect', 'shinyapps.io', and 'RPubs'
Description: Programmatic deployment interface for 'RPubs', 'shinyapps.io', and 'Posit Connect'. Supported content types include R Markdown documents, Shiny applications, Plumber APIs, plots, and static web content.
Author: Aron Atkins [aut, cre], Toph Allen [aut], Hadley Wickham [aut], Jonathan McPherson [aut], JJ Allaire [aut], Posit Software, PBC [cph, fnd]
Maintainer: Aron Atkins <aron@posit.co>

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Package forestplot updated to version 3.1.6 with previous version 3.1.5 dated 2024-10-11

Title: Advanced Forest Plot Using 'grid' Graphics
Description: Allows the creation of forest plots with advanced features, such as multiple confidence intervals per row, customizable fonts for individual text elements, and flexible confidence interval drawing. It also supports mixing text with mathematical expressions. The package extends the application of forest plots beyond traditional meta-analyses, offering a more general version of the original 'rmeta' package’s forestplot() function. It relies heavily on the 'grid' package for rendering the plots.
Author: Max Gordon [aut, cre], Thomas Lumley [aut, ctb]
Maintainer: Max Gordon <max@gforge.se>

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Package findpython updated to version 1.0.9 with previous version 1.0.8 dated 2023-03-14

Title: Functions to Find an Acceptable Python Binary
Description: Package designed to find an acceptable python binary.
Author: Trevor L. Davis [aut, cre] , Paul Gilbert [aut]
Maintainer: Trevor L. Davis <trevor.l.davis@gmail.com>

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