Tue, 16 May 2023

Package episensr updated to version 1.2.0 with previous version 1.1.0 dated 2021-08-20

Title: Basic Sensitivity Analysis of Epidemiological Results
Description: Basic sensitivity analysis of the observed relative risks adjusting for unmeasured confounding and misclassification of the exposure/outcome, or both. It follows the bias analysis methods and examples from the book by Lash T.L, Fox M.P, and Fink A.K. "Applying Quantitative Bias Analysis to Epidemiologic Data", ('Springer', 2021).
Author: Denis Haine [aut, cre]
Maintainer: Denis Haine <denis.haine@gmail.com>

Diff between episensr versions 1.1.0 dated 2021-08-20 and 1.2.0 dated 2023-05-16

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Package spsurvey updated to version 5.5.0 with previous version 5.4.1 dated 2023-01-16

Title: Spatial Sampling Design and Analysis
Description: A design-based approach to statistical inference, with a focus on spatial data. Spatially balanced samples are selected using the Generalized Random Tessellation Stratified (GRTS) algorithm. The GRTS algorithm can be applied to finite resources (point geometries) and infinite resources (linear / linestring and areal / polygon geometries) and flexibly accommodates a diverse set of sampling design features, including stratification, unequal inclusion probabilities, proportional (to size) inclusion probabilities, legacy (historical) sites, a minimum distance between sites, and two options for replacement sites (reverse hierarchical order and nearest neighbor). Data are analyzed using a wide range of analysis functions that perform categorical variable analysis, continuous variable analysis, attributable risk analysis, risk difference analysis, relative risk analysis, change analysis, and trend analysis. spsurvey can also be used to summarize objects, visualize objects, select samples that [...truncated...]
Author: Michael Dumelle [aut, cre] , Tom Kincaid [aut], Tony Olsen [aut], Marc Weber [aut], Don Stevens [ctb], Denis White [ctb]
Maintainer: Michael Dumelle <Dumelle.Michael@epa.gov>

Diff between spsurvey versions 5.4.1 dated 2023-01-16 and 5.5.0 dated 2023-05-16

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Package webfakes updated to version 1.2.0 with previous version 1.1.7 dated 2023-02-08

Title: Fake Web Apps for HTTP Testing
Description: Create a web app that makes it easier to test web clients without using the internet. It includes a web app framework with path matching, parameters and templates. Can parse various 'HTTP' request bodies. Can send 'JSON' data or files from the disk. Includes a web app that implements the 'httpbin.org' web service.
Author: Gabor Csardi [aut, cre], RStudio, Pbc. [cph, fnd], Civetweb contributors [ctb] , Redoc contributors [ctb] , L. Peter Deutsch [ctb] , Martin Purschke [ctb] , Aladdin Enterprises [cph] , Maelle Salmon [ctb]
Maintainer: Gabor Csardi <csardi.gabor@gmail.com>

Diff between webfakes versions 1.1.7 dated 2023-02-08 and 1.2.0 dated 2023-05-16

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Package hdme updated to version 0.6.0 with previous version 0.5.1 dated 2023-02-28

Title: High-Dimensional Regression with Measurement Error
Description: Penalized regression for generalized linear models for measurement error problems (aka. errors-in-variables). The package contains a version of the lasso (L1-penalization) which corrects for measurement error (Sorensen et al. (2015) <doi:10.5705/ss.2013.180>). It also contains an implementation of the Generalized Matrix Uncertainty Selector, which is a version the (Generalized) Dantzig Selector for the case of measurement error (Sorensen et al. (2018) <doi:10.1080/10618600.2018.1425626>).
Author: Oystein Sorensen [aut, cre]
Maintainer: Oystein Sorensen <oystein.sorensen.1985@gmail.com>

Diff between hdme versions 0.5.1 dated 2023-02-28 and 0.6.0 dated 2023-05-16

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New package navigation with initial version 0.0.1
Package: navigation
Title: Analyze the Impact of Sensor Error Modelling on Navigation Performance
Version: 0.0.1
LazyData: true
SystemRequirements: GNU make
LazyDataCompression: xz
Maintainer: Lionel Voirol <lionelvoirol@hotmail.com>
Description: Implements the framework presented in Cucci, D. A., Voirol, L., Khaghani, M. and Guerrier, S. (2023) <doi:10.1109/TIM.2023.3267360> which allows to analyze the impact of sensor error modeling on the performance of integrated navigation (sensor fusion) based on inertial measurement unit (IMU), Global Positioning System (GPS), and barometer data. The framework relies on Monte Carlo simulations in which a Vanilla Extended Kalman filter is coupled with realistic and user-configurable noise generation mechanisms to recover a reference trajectory from noisy measurements. The evaluation of several statistical metrics of the solution, aggregated over hundreds of simulated realizations, provides reasonable estimates of the expected performances of the system in real-world conditions.
Depends: R (>= 4.0.0), plotly, magrittr, simts
License: AGPL-3
Imports: expm, rbenchmark, leaflet, MASS, pbmcapply, Rcpp (>= 0.8.0), RcppArmadillo (>= 0.2.0)
Encoding: UTF-8
Suggests: knitr, rmarkdown
VignetteBuilder: knitr
URL: https://github.com/SMAC-Group/navigation
BugReports: https://github.com/SMAC-Group/navigation/issues
LinkingTo: Rcpp, RcppArmadillo
NeedsCompilation: yes
Packaged: 2023-05-16 09:06:11 UTC; lionel
Author: Davide A. Cucci [aut], Lionel Voirol [aut, cre], Mehran Khaghani [aut], Stephane Guerrier [aut]
Repository: CRAN
Date/Publication: 2023-05-16 17:50:02 UTC

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Package hwep updated to version 2.0.2 with previous version 2.0.1 dated 2023-03-15

Title: Hardy-Weinberg Equilibrium in Polyploids
Description: Inference concerning equilibrium and random mating in autopolyploids. Methods are available to test for equilibrium and random mating at any even ploidy level (>2) in the presence of double reduction at biallelic loci. For autopolyploid populations in equilibrium, methods are available to estimate the degree of double reduction. We also provide functions to calculate genotype frequencies at equilibrium, or after one or several rounds of random mating, given rates of double reduction. The main function is hwefit(). This material is based upon work supported by the National Science Foundation under Grant No. 2132247. The opinions, findings, and conclusions or recommendations expressed are those of the author and do not necessarily reflect the views of the National Science Foundation. For details of these methods, see Gerard (2022a) <doi:10.1111/biom.13722> and Gerard (2022b) <doi:10.1101/2022.08.11.503635>.
Author: David Gerard [aut, cre] , NSF DBI 2132247 [fnd]
Maintainer: David Gerard <gerard.1787@gmail.com>

Diff between hwep versions 2.0.1 dated 2023-03-15 and 2.0.2 dated 2023-05-16

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New package compindPCA with initial version 0.1.0
Package: compindPCA
Title: Computation of Relative Weights of Variables and Composite Index Values Based on PCA
Version: 0.1.0
Maintainer: Rajeev Ranjan Kumar <rrk.uasd@gmail.com>
Description: It helps in development of a principal component analysis based composite index by assigning weights to variables and combining the weighted variables. For method details see Sendhil, R., Jha, A., Kumar, A. and Singh, S. (2018). <doi:10.1016/j.ecolind.2018.02.053>, and Wu, T. (2021). <doi:10.1016/j.ecolind.2021.108006>.
License: GPL-3
Encoding: UTF-8
LazyData: true
Imports: factoextra
Depends: R (>= 2.10)
NeedsCompilation: no
Packaged: 2023-05-16 11:08:59 UTC; user
Author: Sudipta Paul [aut, ctb], Rajeev Ranjan Kumar [aut, cre], Mrinmoy Ray [ctb], Biswajit Mondal [ctb], Prakash Kumar [ctb]
Repository: CRAN
Date/Publication: 2023-05-16 17:50:06 UTC

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Package vetiver updated to version 0.2.1 with previous version 0.2.0 dated 2023-01-26

Title: Version, Share, Deploy, and Monitor Models
Description: The goal of 'vetiver' is to provide fluent tooling to version, share, deploy, and monitor a trained model. Functions handle both recording and checking the model's input data prototype, and predicting from a remote API endpoint. The 'vetiver' package is extensible, with generics that can support many kinds of models.
Author: Julia Silge [cre, aut] , Posit Software, PBC [cph, fnd]
Maintainer: Julia Silge <julia.silge@posit.co>

Diff between vetiver versions 0.2.0 dated 2023-01-26 and 0.2.1 dated 2023-05-16

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New package OpenRepGrid with initial version 0.1.14
Package: OpenRepGrid
License: GPL (>= 2)
Title: Tools to Analyze Repertory Grid Data
LazyData: yes
LazyLoad: yes
Description: Analyze repertory grids, a qualitative-quantitative data collection technique devised by George A. Kelly in the 1950s. Today, grids are used across various domains ranging from clinical psychology to marketing. The package contains functions to quantitatively analyze and visualize repertory grid data.
Version: 0.1.14
Date: 2023-05-16
Encoding: UTF-8
URL: https://github.com/markheckmann/OpenRepGrid
Imports: methods, graphics, grid, utils, stats, grDevices, crayon, plyr, stringr, abind, rgl, colorspace, psych, XML, pvclust, openxlsx, tidyr, dplyr, scales, igraph
NeedsCompilation: no
Suggests: testthat (>= 2.1.0), covr
Packaged: 2023-05-16 13:47:30 UTC; MarkHeckmann
Author: Mark Heckmann [aut, cre, cph] , Alejandro Garcia Gutierrez [ctb], Diego Vitali [ctb]
Maintainer: Mark Heckmann <heckmann.mark@gmail.com>
Repository: CRAN
Date/Publication: 2023-05-16 15:00:11 UTC

More information about OpenRepGrid at CRAN
Permanent link

Package highs updated to version 0.1-10 with previous version 0.1-6 dated 2022-12-15

Title: 'HiGHS' Optimization Solver
Description: R interface to 'HiGHS', an optimization solver for solving mixed integer optimization problems with quadratic or linear objective and linear constraints.
Author: Florian Schwendinger [aut, cre], Dirk Schumacher [aut], Julian Hall [cph], Ivet Galabova [cph], Leona Gottwald [cph], Michael Feldmeier [cph]
Maintainer: Florian Schwendinger <FlorianSchwendinger@gmx.at>

Diff between highs versions 0.1-6 dated 2022-12-15 and 0.1-10 dated 2023-05-16

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More information about highs at CRAN
Permanent link

Package batchmix updated to version 2.0.0 with previous version 1.0.1 dated 2022-06-21

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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More information about batchmix at CRAN
Permanent link

Package basefun updated to version 1.1-4 with previous version 1.1-3 dated 2022-05-25

Title: Infrastructure for Computing with Basis Functions
Description: Some very simple infrastructure for basis functions.
Author: Torsten Hothorn [aut, cre]
Maintainer: Torsten Hothorn <Torsten.Hothorn@R-project.org>

Diff between basefun versions 1.1-3 dated 2022-05-25 and 1.1-4 dated 2023-05-16

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More information about basefun at CRAN
Permanent link

Package valr updated to version 0.6.8 with previous version 0.6.7 dated 2023-02-18

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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More information about valr at CRAN
Permanent link

Package TestGardener updated to version 3.2.3 with previous version 3.1.4 dated 2023-01-15

Title: Optimal Analysis of Test and Rating Scale Data
Description: Develop, evaluate, and score multiple choice examinations, psychological scales, questionnaires, and similar types of data involving sequences of choices among one or more sets of answers. This version of the package should be considered as brand new. Almost all of the functions have been changed, including their argument list. See the file NEWS.Rd in the Inst folder for more information. Using the package does not require any formal statistical knowledge beyond what would be provided by a first course in statistics in a social science department. There the user would encounter the concept of probability and how it is used to model data and make decisions, and would become familiar with basic mathematical and statistical notation. Most of the output is in graphical form.
Author: James Ramsay [aut, cre], Juan Li [ctb], Marie Wiberg [ctb], Joakim Wallmark [ctb], Spencer Graves [ctb]
Maintainer: James Ramsay <james.ramsay@mcgill.ca>

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Package nlrx updated to version 0.4.4 with previous version 0.4.3 dated 2021-09-20

Title: Setup, Run and Analyze 'NetLogo' Model Simulations from 'R' via 'XML'
Description: Setup, run and analyze 'NetLogo' (<https://ccl.northwestern.edu/netlogo/>) model simulations in 'R'. 'nlrx' experiments use a similar structure as 'NetLogos' Behavior Space experiments. However, 'nlrx' offers more flexibility and additional tools for running and analyzing complex simulation designs and sensitivity analyses. The user defines all information that is needed in an intuitive framework, using class objects. Experiments are submitted from 'R' to 'NetLogo' via 'XML' files that are dynamically written, based on specifications defined by the user. By nesting model calls in future environments, large simulation design with many runs can be executed in parallel. This also enables simulating 'NetLogo' experiments on remote high performance computing machines. In order to use this package, 'Java' and 'NetLogo' (>= 5.3.1) need to be available on the executing system.
Author: Jan Salecker [aut] , Marco Sciaini [aut] , Marina Papadopoulou [rev] , Sebastian Hanss [cre]
Maintainer: Sebastian Hanss <nlrx@mailbox.org>

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Package goeveg updated to version 0.6.4 with previous version 0.6.1 dated 2023-05-04

Title: Functions for Community Data and Ordinations
Description: A collection of functions useful in (vegetation) community analyses and ordinations. Includes automatic species selection for ordination diagrams, NMDS stress/scree plots, species response curves and rank-abundance curves as well as calculation and sorting of synoptic tables.
Author: Friedemann von Lampe [aut, cre], Jenny Schellenberg [aut]
Maintainer: Friedemann von Lampe <fvonlampe@uni-goettingen.de>

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Package geojsonio updated to version 0.11.1 with previous version 0.11.0 dated 2023-03-08

Title: Convert Data from and to 'GeoJSON' or 'TopoJSON'
Description: Convert data to 'GeoJSON' or 'TopoJSON' from various R classes, including vectors, lists, data frames, shape files, and spatial classes. 'geojsonio' does not aim to replace packages like 'sp', 'rgdal', 'rgeos', but rather aims to be a high level client to simplify conversions of data from and to 'GeoJSON' and 'TopoJSON'.
Author: Scott Chamberlain [aut], Andy Teucher [aut], Michael Mahoney [aut, cre]
Maintainer: Michael Mahoney <mike.mahoney.218@gmail.com>

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Package rcrypt (with last version 0.1.1) was removed from CRAN

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

2015-09-20 0.1.1
2015-09-05 0.1.0

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Package via updated to version 0.2.0 with previous version 0.1.0 dated 2023-03-15

Title: Virtual Arrays
Description: The base class 'VirtualArray' is defined, which acts as a wrapper around lists allowing users to fold arbitrary sequential data into n-dimensional, R-style virtual arrays. The derived 'XArray' class is defined to be used for homogeneous lists that contain a single class of objects. The 'RasterArray' and 'SfArray' classes enable the use of stacked spatial data instead of lists.
Author: Adam T. Kocsis [cre, aut] , Deutsche Forschungsgemeinschaft [fnd], FAU GeoZentrum Nordbayern [fnd]
Maintainer: Adam T. Kocsis <adam.t.kocsis@gmail.com>

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Package parSim updated to version 0.1.5 with previous version 0.1.4 dated 2020-07-10

Title: Parallel Simulation Studies
Description: Perform flexible simulation studies using one or multiple computer cores. The package is set up to be usable on high-performance clusters in addition to being run locally, see examples on <https://github.com/SachaEpskamp/parSim>.
Author: Sacha Epskamp
Maintainer: Sacha Epskamp <mail@sachaepskamp.com>

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Package mlVAR updated to version 0.5.1 with previous version 0.5 dated 2021-10-25

Title: Multi-Level Vector Autoregression
Description: Estimates the multi-level vector autoregression model on time-series data. Three network structures are obtained: temporal networks, contemporaneous networks and between-subjects networks.
Author: Sacha Epskamp [aut, cre], Marie K. Deserno [aut], Laura F. Bringmann [aut], Myrthe Veenman [ctb]
Maintainer: Sacha Epskamp <mail@sachaepskamp.com>

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Package graphicalVAR updated to version 0.3.1 with previous version 0.3 dated 2021-10-19

Title: Graphical VAR for Experience Sampling Data
Description: Estimates within and between time point interactions in experience sampling data, using the Graphical vector autoregression model in combination with regularization. See also Epskamp, Waldorp, Mottus & Borsboom (2018) <doi:10.1080/00273171.2018.1454823>.
Author: Sacha Epskamp [aut, cre], Eren Asena [ctb]
Maintainer: Sacha Epskamp <mail@sachaepskamp.com>

Diff between graphicalVAR versions 0.3 dated 2021-10-19 and 0.3.1 dated 2023-05-16

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Package declared updated to version 0.21 with previous version 0.20 dated 2023-03-03

Title: Functions for Declared Missing Values
Description: A zero dependency package containing functions to declare labels and missing values, coupled with associated functions to create (weighted) tables of frequencies and various other summary measures. Some of the base functions have been rewritten to make use of the specific information about the missing values, most importantly to distinguish between empty and declared missing values. Some functions have similar functionality with the corresponding ones from packages "haven" and "labelled". The aim is to ensure as much compatibility as possible with these packages, while offering an alternative in the objects of class "declared".
Author: Adrian Dusa [aut, cre, cph] , Daniel Antal [ctb]
Maintainer: Adrian Dusa <dusa.adrian@unibuc.ro>

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Package BiDAG updated to version 2.1.4 with previous version 2.1.3 dated 2023-01-23

Title: Bayesian Inference for Directed Acyclic Graphs
Description: Implementation of a collection of MCMC methods for Bayesian structure learning of directed acyclic graphs (DAGs), both from continuous and discrete data. For efficient inference on larger DAGs, the space of DAGs is pruned according to the data. To filter the search space, the algorithm employs a hybrid approach, combining constraint-based learning with search and score. A reduced search space is initially defined on the basis of a skeleton obtained by means of the PC-algorithm, and then iteratively improved with search and score. Search and score is then performed following two approaches: Order MCMC, or Partition MCMC. The BGe score is implemented for continuous data and the BDe score is implemented for binary data or categorical data. The algorithms may provide the maximum a posteriori (MAP) graph or a sample (a collection of DAGs) from the posterior distribution given the data. All algorithms are also applicable for structure learning and sampling for dynamic Bayesian networks. Refe [...truncated...]
Author: Polina Suter [aut, cre], Jack Kuipers [aut]
Maintainer: Polina Suter <polina.suter@gmail.com>

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Package ARDL updated to version 0.2.3 with previous version 0.2.2 dated 2023-02-09

Title: ARDL, ECM and Bounds-Test for Cointegration
Description: Creates complex autoregressive distributed lag (ARDL) models and constructs the underlying unrestricted and restricted error correction model (ECM) automatically, just by providing the order. It also performs the bounds-test for cointegration as described in Pesaran et al. (2001) <doi:10.1002/jae.616> and provides the multipliers and the cointegrating equation. The validity and the accuracy of this package have been verified by successfully replicating the results of Pesaran et al. (2001) in Natsiopoulos and Tzeremes (2022) <doi:10.1002/jae.2919>.
Author: Kleanthis Natsiopoulos [aut, cre] , Nickolaos Tzeremes [aut]
Maintainer: Kleanthis Natsiopoulos <klnatsio@gmail.com>

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Package semPower updated to version 2.0.1 with previous version 2.0.0 dated 2023-05-15

Title: Power Analyses for SEM
Description: Provides a-priori, post-hoc, and compromise power-analyses for structural equation models (SEM).
Author: Morten Moshagen [aut, cre] , Martina Bader [aut]
Maintainer: Morten Moshagen <morten.moshagen@uni-ulm.de>

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Package rfacebookstat updated to version 2.9.3 with previous version 2.9.2 dated 2023-04-20

Title: Load Data from Facebook API Marketing
Description: Load data by campaigns, ads, ad sets and insights, ad account and business manager from Facebook Marketing API into R. For more details see official documents by Facebook Marketing API <https://developers.facebook.com/docs/marketing-apis/>.
Author: Alexey Seleznev [aut, cre]
Maintainer: Alexey Seleznev <selesnow@gmail.com>

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Package realtest updated to version 0.2.3 with previous version 0.2.1 dated 2021-06-17

Title: Where Expectations Meet Reality: Realistic Unit Testing
Description: A framework for unit testing for realistic minimalists, where we distinguish between expected, acceptable, current, fallback, ideal, or regressive behaviour. It can also be used for monitoring third-party software projects for changes.
Author: Marek Gagolewski [aut, cre, cph]
Maintainer: Marek Gagolewski <marek@gagolewski.com>

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Package orloca updated to version 5.3 with previous version 4.10 dated 2020-09-27

Title: Operations Research LOCational Analysis Models
Description: Objects and methods to handle and solve the min-sum location problem, also known as Fermat-Weber problem. The min-sum location problem search for a point such that the weighted sum of the distances to the demand points are minimized. See "The Fermat-Weber location problem revisited" by Brimberg, Mathematical Programming, 1, pg. 71-76, 1995. <DOI:10.1007/BF01592245>. General global optimization algorithms are used to solve the problem, along with the adhoc Weiszfeld method, see "Sur le point pour lequel la Somme des distances de n points donnes est minimum", by Weiszfeld, Tohoku Mathematical Journal, First Series, 43, pg. 355-386, 1937 or "On the point for which the sum of the distances to n given points is minimum", by E. Weiszfeld and F. Plastria, Annals of Operations Research, 167, pg. 7-41, 2009. <DOI:10.1007/s10479-008-0352-z>.
Author: Manuel Munoz-Marquez <manuel.munoz@uca.es>
Maintainer: Manuel Munoz-Marquez <manuel.munoz@uca.es>

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Package mwcsr updated to version 0.1.7 with previous version 0.1.6 dated 2022-07-12

Title: Solvers for Maximum Weight Connected Subgraph Problem and Its Variants
Description: Algorithms for solving various Maximum Weight Connected Subgraph Problems, including variants with budget constraints, cardinality constraints, weighted edges and signals. The package represents an R interface to high-efficient solvers based on relax-and-cut approach (Álvarez-Miranda E., Sinnl M. (2017) <doi:10.1016/j.cor.2017.05.015>) mixed-integer programming (Loboda A., Artyomov M., and Sergushichev A. (2016) <doi:10.1007/978-3-319-43681-4_17>) and simulated annealing.
Author: Alexander Loboda [aut, cre], Nikolay Poperechnyi [aut], Eduardo Alvarez-Miranda [aut], Markus Sinnl [aut], Alexey Sergushichev [aut], Paul Hosler Jr. [cph] , www.hamcrest.org [cph] , Barak Naveh and Contributors [cph] , The Apache Software Foundation [...truncated...]
Maintainer: Alexander Loboda <aleks.loboda@gmail.com>

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Package bootnet updated to version 1.5.1 with previous version 1.5 dated 2021-10-25

Title: Bootstrap Methods for Various Network Estimation Routines
Description: Bootstrap methods to assess accuracy and stability of estimated network structures and centrality indices <doi:10.3758/s13428-017-0862-1>. Allows for flexible specification of any undirected network estimation procedure in R, and offers default sets for various estimation routines.
Author: Sacha Epskamp [aut, cre], Eiko I. Fried [ctb]
Maintainer: Sacha Epskamp <mail@sachaepskamp.com>

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Package ustfd updated to version 0.4.0 with previous version 0.2.0 dated 2022-10-31

Title: API Client for US Treasury Fiscal Data
Description: Make requests from the US Treasury Fiscal Data API endpoints.
Author: Guillermo Roditi Dominguez [aut, cre]
Maintainer: Guillermo Roditi Dominguez <guillermo@newriverinvestments.com>

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Package qgraph updated to version 1.9.5 with previous version 1.9.4 dated 2023-03-20

Title: Graph Plotting Methods, Psychometric Data Visualization and Graphical Model Estimation
Description: Fork of qgraph - Weighted network visualization and analysis, as well as Gaussian graphical model computation. See Epskamp et al. (2012) <doi:10.18637/jss.v048.i04>.
Author: Sacha Epskamp [aut, cre], Giulio Costantini [aut], Jonas Haslbeck [aut], Adela Isvoranu [aut], Angelique O. J. Cramer [ctb], Lourens J. Waldorp [ctb], Verena D. Schmittmann [ctb], Denny Borsboom [ctb]
Maintainer: Sacha Epskamp <mail@sachaepskamp.com>

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Package QCA updated to version 3.19 with previous version 3.18 dated 2023-02-03

Title: Qualitative Comparative Analysis
Description: An extensive set of functions to perform Qualitative Comparative Analysis: crisp sets ('csQCA'), temporal ('tQCA'), multi-value ('mvQCA') and fuzzy sets ('fsQCA'), using a GUI - graphical user interface. 'QCA' is a methodology that bridges the qualitative and quantitative divide in social science research. It uses a Boolean minimization algorithm, resulting in a minimal causal configuration associated with a given phenomenon.
Author: Adrian Dusa [aut, cre, cph] , Ciprian Paduraru [ctb] , jQuery Foundation [cph] , jQuery contributors [ctb, cph] , lp_solve [cph] , Vasil Dinkov [ctb, cph] , Dmitry Baranovskiy [ctb, cph] , Emmanuel Quentin [ctb, cph] , Jimmy Breck-McKye [ctb, cph] , [...truncated...]
Maintainer: Adrian Dusa <dusa.adrian@unibuc.ro>

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Package multilevLCA updated to version 1.2 with previous version 1.1 dated 2023-03-17

Title: Estimates and Plots Single-Level and Multilevel Latent Class Models
Description: Efficiently estimates single- and multilevel latent class models with covariates, allowing for output visualization in all specifications. For more technical details, see Lyrvall et al (2023) <arXiv:2305.07276>.
Author: Roberto Di Mari [aut, cre], Johan Lyrvall [aut], Zsuzsa Bakk [ctb], Jennifer Oser [ctb], Jouni Kuha [ctb]
Maintainer: Roberto Di Mari <roberto.dimari@unict.it>

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Package markdown updated to version 1.7 with previous version 1.6 dated 2023-04-07

Title: Render Markdown with 'commonmark'
Description: Render Markdown to full and lightweight HTML/LaTeX documents with the 'commonmark' package. It also supports features that are missing in 'commonmark', such as raw HTML/LaTeX blocks, LaTeX math, superscripts, subscripts, footnotes, element attributes, appendices, and fenced 'Divs'. With additional JavaScript and CSS, it can also create HTML slides and articles.
Author: Yihui Xie [aut, cre] , JJ Allaire [aut], Jeffrey Horner [aut], Henrik Bengtsson [ctb], Jim Hester [ctb], Yixuan Qiu [ctb], Kohske Takahashi [ctb], Adam November [ctb], Nacho Caballero [ctb], Jeroen Ooms [ctb], Thomas Leeper [ctb], Joe Cheng [ctb], An [...truncated...]
Maintainer: Yihui Xie <xie@yihui.name>

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New package wcox with initial version 1.0
Package: wcox
Title: Weights to Correct for Outcome Dependent Sampling in Time to Event Data
Version: 1.0
Description: A new inverse probability of selection weighted Cox model to deal with outcome-dependent sampling in survival analysis.
License: GPL-3
Encoding: UTF-8
LazyData: true
Imports: dplyr, tidyr, survival, stats
Suggests: knitr, rmarkdown, testthat (>= 3.0.0)
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2023-05-15 14:59:26 UTC; veraarntzen
Author: Vera Arntzen [aut, cre] , Mar Rodriguez-Girondo [aut]
Maintainer: Vera Arntzen <v.h.arntzen@math.leidenuniv.nl>
Depends: R (>= 3.5.0)
Repository: CRAN
Date/Publication: 2023-05-16 08:30:02 UTC

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New package validateIt with initial version 1.2.1
Package: validateIt
Title: Validating Topic Coherence and Topic Labels
Version: 1.2.1
Description: By creating crowd-sourcing tasks that can be easily posted and results retrieved using Amazon's Mechanical Turk (MTurk) API, researchers can use this solution to validate the quality of topics obtained from unsupervised or semi-supervised learning methods, and the relevance of topic labels assigned. This helps ensure that the topic modeling results are accurate and useful for research purposes. See Ying and others (2022) <doi:10.1101/2023.05.02.538599>. For more information, please visit <https://github.com/Triads-Developer/Topic_Model_Validation>.
License: GPL (>= 2)
Encoding: UTF-8
LazyData: true
Imports: pyMTurkR, rlang (>= 0.4.11), tm (>= 0.7-11), here, SnowballC
Suggests: roxygen2, testthat
Author: Luwei Ying [aut, cre] , Jacob Montgomery [aut], Brandon Stewart [aut]
Maintainer: Luwei Ying <triads.developers@wustl.edu>
Repository: CRAN
Depends: R (>= 3.5.0)
NeedsCompilation: no
Packaged: 2023-05-15 12:34:05 UTC; jessiewalker
Date/Publication: 2023-05-16 08:20:02 UTC

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New package isopleuros with initial version 1.0.0
Package: isopleuros
Title: Ternary Plots
Version: 1.0.0
Maintainer: Nicolas Frerebeau <nicolas.frerebeau@u-bordeaux-montaigne.fr>
Description: Ternary plots made simple. This package allows to create ternary plots using 'graphics'. It provides functions to display the data in the ternary space, to add or tune graphical elements and to display statistical summaries. It also includes common ternary diagrams which are useful for the archaeologist (e.g. soil texture charts, ceramic phase diagram).
License: GPL (>= 3)
URL: https://packages.tesselle.org/isopleuros/, https://github.com/tesselle/isopleuros
BugReports: https://github.com/tesselle/isopleuros/issues
Depends: R (>= 2.10)
Imports: graphics, grDevices, methods, utils
Suggests: akima, testthat (>= 3.0.0), vdiffr (>= 1.0.0)
Encoding: UTF-8
LazyData: true
NeedsCompilation: no
Packaged: 2023-05-15 22:24:57 UTC; nicolas
Author: Nicolas Frerebeau [aut, cre] , Brice Lebrun [ctb]
Repository: CRAN
Date/Publication: 2023-05-16 08:40:02 UTC

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Package FoReco updated to version 0.2.6 with previous version 0.2.5 dated 2022-07-04

Title: Forecast Reconciliation
Description: Classical (bottom-up and top-down), optimal and heuristic combination forecast point (Di Fonzo and Girolimetto, 2023) <doi:10.1016/j.ijforecast.2021.08.004> and probabilistic (Girolimetto et al. 2023) <arXiv:2303.17277> reconciliation procedures for cross-sectional, temporal, and cross-temporal linearly constrained time series.
Author: Daniele Girolimetto [aut, cre, fnd] , Tommaso Di Fonzo [aut, fnd]
Maintainer: Daniele Girolimetto <daniele.girolimetto@phd.unipd.it>

Diff between FoReco versions 0.2.5 dated 2022-07-04 and 0.2.6 dated 2023-05-16

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New package drcSeedGerm with initial version 1.0.1
Package: drcSeedGerm
Date: 2023-04-20
Title: Utilities for Data Analyses in Seed Germination/Emergence Assays
Version: 1.0.1
Depends: R (>= 3.5.0), drc, drcte
Imports: plyr, dplyr, mvtnorm, survival
Author: Andrea Onofri <andrea.onofri@unipg.it>
Maintainer: Andrea Onofri <andrea.onofri@unipg.it>
Description: Utility functions to be used to analyse datasets obtained from seed germination/emergence assays. Fits several types of seed germination/emergence models, including those reported in Onofri et al. (2018) "Hydrothermal-time-to-event models for seed germination", European Journal of Agronomy, 101, 129-139 <doi:10.1016/j.eja.2018.08.011>. Contains several datasets for practicing.
URL: https://www.statforbiology.com
License: GPL (>= 2)
Encoding: UTF-8
LazyData: true
NeedsCompilation: no
Packaged: 2023-05-15 14:26:00 UTC; andrea
Repository: CRAN
Date/Publication: 2023-05-16 08:30:05 UTC

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New package baldur with initial version 0.0.1
Package: baldur
Title: Bayesian Hierarchical Modeling for Label-Free Proteomics
Version: 0.0.1
Description: Statistical decision in proteomics data using a hierarchical Bayesian model. There are two regression models for describing the mean-variance trend, a gamma regression or a latent gamma mixture regression. The regression model is then used as an Empirical Bayes estimator for the prior on the variance in a peptide. Further, it assumes that each measurement has an uncertainty (increased variance) associated with it that is also inferred. Finally, it tries to estimate the posterior distribution (by Hamiltonian Monte Carlo) for the differences in means for each peptide in the data. Once the posterior is inferred, it integrates the tails to estimate the probability of error from which a statistical decision can be made.
License: MIT + file LICENSE
URL: https://www.biorxiv.org/content/10.1101/2023.05.11.540411v1
Encoding: UTF-8
Language: en-US
Biarch: true
Depends: R (>= 4.2.0)
Imports: dplyr (>= 1.0.9), magrittr (>= 2.0.3), methods, purrr (>= 0.3.4), Rcpp (>= 0.12.0), RcppParallel (>= 5.0.1), rstan (>= 2.18.1), rstantools (>= 2.2.0), stats, stringr (>= 1.0.4), tidyr (>= 1.2.0), rlang (>= 1.0.2), Rdpack (>= 2.4), multidplyr (>= 0.1.1), ggplot2 (>= 3.3.6), tibble (>= 3.1.7), viridisLite (>= 0.4.1), lifecycle
LinkingTo: BH (>= 1.66.0), Rcpp (>= 0.12.0), RcppEigen (>= 0.3.3.3.0), RcppParallel (>= 5.0.1), rstan (>= 2.18.1), StanHeaders (>= 2.18.0)
SystemRequirements: GNU make
Suggests: knitr, rmarkdown
VignetteBuilder: knitr
LazyData: true
NeedsCompilation: yes
Packaged: 2023-05-15 20:49:41 UTC; Pberg
Author: Philip Berg [aut, cre]
Maintainer: Philip Berg <pb1015@msstate.edu>
Repository: CRAN
Date/Publication: 2023-05-16 08:40:07 UTC

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Package likelihoodR updated to version 1.1.1 with previous version 1.1.0 dated 2023-03-15

Title: Likelihood Analyses for Common Statistical Tests
Description: A collection of functions that calculate the log likelihood (support) for a range of statistical tests. Where possible the likelihood function and likelihood interval for the observed data are displayed. The evidential approach used here is based on the book "Likelihood" by A.W.F. Edwards (1992, ISBN-13 : 978-0801844430), "Statistical Evidence" by R. Royall (1997, ISBN-13 : 978-0412044113), S.N. Goodman & R. Royall (2011) <doi:10.2105/AJPH.78.12.1568>, "Understanding Psychology as a Science" by Z. Dienes (2008, ISBN-13 : 978-0230542310), S. Glover & P. Dixon <https://link.springer.com/article/10.3758/BF03196706> and others. This package accompanies "Evidence-Based Statistics" by P. Cahusac (2020, ISBN-13 : 978-1119549802).
Author: Peter Cahusac [aut, cre]
Maintainer: Peter Cahusac <peteqsac@gmail.com>

Diff between likelihoodR versions 1.1.0 dated 2023-03-15 and 1.1.1 dated 2023-05-16

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Package influential updated to version 2.2.7 with previous version 2.2.6 dated 2022-08-06

Title: Identification and Classification of the Most Influential Nodes
Description: Contains functions for the classification and ranking of top candidate features, reconstruction of networks from adjacency matrices and data frames, analysis of the topology of the network and calculation of centrality measures, and identification of the most influential nodes. Also, a function is provided for running SIRIR model, which is the combination of leave-one-out cross validation technique and the conventional SIR model, on a network to unsupervisedly rank the true influence of vertices. Additionally, some functions have been provided for the assessment of dependence and correlation of two network centrality measures as well as the conditional probability of deviation from their corresponding means in opposite direction. Fred Viole and David Nawrocki (2013, ISBN:1490523995). Csardi G, Nepusz T (2006). "The igraph software package for complex network research." InterJournal, Complex Systems, 1695. Adopted algorithms and sources are referenced in function document.
Author: Abbas Salavaty [aut, cre], Mirana Ramialison [ths], Peter D. Currie [ths]
Maintainer: Adrian Salavaty <abbas.salavaty@gmail.com>

Diff between influential versions 2.2.6 dated 2022-08-06 and 2.2.7 dated 2023-05-16

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Package gmmsslm updated to version 1.1.4 with previous version 1.1.2 dated 2023-02-25

Title: Semi-Supervised Gaussian Mixture Model with a Missing-Data Mechanism
Description: The algorithm of semi-supervised learning is based on finite Gaussian mixture models and includes a mechanism for handling missing data. It aims to fit a g-class Gaussian mixture model using maximum likelihood. The algorithm treats the labels of unclassified features as missing data, building on the framework introduced by Rubin (1976) <doi:10.2307/2335739> for missing data analysis. By taking into account the dependencies in the missing pattern, the algorithm provides more information for determining the optimal classifier, as specified by Bayes' rule.
Author: Ziyang Lyu [aut, cre], Daniel Ahfock [aut], Ryan Thompson [aut], Geoffrey J. McLachlan [aut]
Maintainer: Ziyang Lyu <ziyang.lyu@unsw.edu.au>

Diff between gmmsslm versions 1.1.2 dated 2023-02-25 and 1.1.4 dated 2023-05-16

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Package blogdown updated to version 1.17 with previous version 1.16 dated 2022-12-13

Title: Create Blogs and Websites with R Markdown
Description: Write blog posts and web pages in R Markdown. This package supports the static site generator 'Hugo' (<https://gohugo.io>) best, and it also supports 'Jekyll' (<https://jekyllrb.com>) and 'Hexo' (<https://hexo.io>).
Author: Yihui Xie [aut, cre] , Christophe Dervieux [aut] , Alison Presmanes Hill [aut] , Amber Thomas [ctb], Beilei Bian [ctb], Brandon Greenwell [ctb], Brian Barkley [ctb], Deependra Dhakal [ctb], Eric Nantz [ctb], Forest Fang [ctb], Garrick Aden-Buie [ctb] [...truncated...]
Maintainer: Yihui Xie <xie@yihui.name>

Diff between blogdown versions 1.16 dated 2022-12-13 and 1.17 dated 2023-05-16

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Package hightR updated to version 0.3.0 with previous version 0.2.0 dated 2023-04-17

Title: HIGHT Algorithm
Description: HIGHT(HIGh security and light weigHT) algorithm is a block cipher encryption algorithm developed to provide confidentiality in computing environments that demand low power consumption and lightweight, such as RFID(Radio-Frequency Identification) and USN(Ubiquitous Sensor Network), or in mobile environments that require low power consumption and lightweight, such as smartphones and smart cards. Additionally, it is designed with a simple structure that enables it to be used with basic arithmetic operations, XOR, and circular shifts in 8-bit units. This algorithm was designed to consider both safety and efficiency in a very simple structure suitable for limited environments, compared to the former 128-bit encryption algorithm SEED. In December 2010, it became an ISO(International Organization for Standardization) standard. The detailed procedure is described in Hong et al. (2006) <doi:10.1007/11894063_4>.
Author: Yongwoo Kim [aut, cre]
Maintainer: Yongwoo Kim <yw_kim@outlook.com>

Diff between hightR versions 0.2.0 dated 2023-04-17 and 0.3.0 dated 2023-05-16

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Package CausalGPS updated to version 0.3.1 with previous version 0.3.0 dated 2023-02-15

Title: Matching on Generalized Propensity Scores with Continuous Exposures
Description: Provides a framework for estimating causal effects of a continuous exposure using observational data, and implementing matching and weighting on the generalized propensity score. Wu, X., Mealli, F., Kioumourtzoglou, M.A., Dominici, F. and Braun, D., 2022. Matching on generalized propensity scores with continuous exposures. Journal of the American Statistical Association, pp.1-29.
Author: Naeem Khoshnevis [aut, cre] , Xiao Wu [aut] , Danielle Braun [aut]
Maintainer: Naeem Khoshnevis <nkhoshnevis@g.harvard.edu>

Diff between CausalGPS versions 0.3.0 dated 2023-02-15 and 0.3.1 dated 2023-05-16

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