Wed, 10 May 2023

Package tmsens updated to version 0.3.0 with previous version 0.2.0 dated 2023-03-30

Title: Sensitivity Analysis Using the Trimmed Means Estimator
Description: Sensitivity analysis using the trimmed means estimator.
Author: Audinga-Dea Hazewinkel [aut, cre] , Tom Palmer [aut] , Kate Tilling [aut] , Kaitlin Wade [aut] , Jack Bowden [aut]
Maintainer: Audinga-Dea Hazewinkel <dea.hazew@gmail.com>

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Package grf updated to version 2.3.0 with previous version 2.2.1 dated 2022-12-14

Title: Generalized Random Forests
Description: Forest-based statistical estimation and inference. GRF provides non-parametric methods for heterogeneous treatment effects estimation (optionally using right-censored outcomes, multiple treatment arms or outcomes, or instrumental variables), as well as least-squares regression, quantile regression, and survival regression, all with support for missing covariates.
Author: Julie Tibshirani [aut, cre], Susan Athey [aut], Rina Friedberg [ctb], Vitor Hadad [ctb], David Hirshberg [ctb], Luke Miner [ctb], Erik Sverdrup [aut], Stefan Wager [aut], Marvin Wright [ctb]
Maintainer: Julie Tibshirani <jtibs@cs.stanford.edu>

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Package scoringRules updated to version 1.1.1 with previous version 1.0.2 dated 2022-09-19

Title: Scoring Rules for Parametric and Simulated Distribution Forecasts
Description: Dictionary-like reference for computing scoring rules in a wide range of situations. Covers both parametric forecast distributions (such as mixtures of Gaussians) and distributions generated via simulation.
Author: Alexander I. Jordan [aut] , Fabian Krueger [aut, cre] , Sebastian Lerch [aut] , Sam Allen [aut], Maximiliane Graeter [ctb]
Maintainer: Fabian Krueger <Fabian.Krueger83@gmail.com>

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Package marble updated to version 0.0.2 with previous version 0.0.1 dated 2023-05-02

Title: Robust Marginal Bayesian Variable Selection for Gene-Environment Interactions
Description: Recently, multiple marginal variable selection methods have been developed and shown to be effective in Gene-Environment interactions studies. We propose a novel marginal Bayesian variable selection method for Gene-Environment interactions studies. In particular, our marginal Bayesian method is robust to data contamination and outliers in the outcome variables. With the incorporation of spike-and-slab priors, we have implemented the Gibbs sampler based on Markov Chain Monte Carlo. The core algorithms of the package have been developed in 'C++'.
Author: Xi Lu [aut, cre], Cen Wu [aut]
Maintainer: Xi Lu <xilu@ksu.edu>

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Package glmnetr updated to version 0.2-0 with previous version 0.1-2 dated 2023-02-18

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'), Recursive Partitioning ('RPART') or step wise regression models are fit. Nested cross validation to estimate and compare performances between these models is also performed. 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 cv.glmnet(). This option is not described in the 'glmnet' Reference Manual but is described in the 'glmnet' "The Relaxed Lasso" vignette. In this package, 'glmnetr', we provide a similar workaround and solve for the non penalized relaxed model where gamma=0 for model structures analogue to 'R' functions like glm() or coxph() of [...truncated...]
Author: Walter K Kremers [aut, cre] , Nicholas B Larson [ctb]
Maintainer: Walter K Kremers <kremers.walter@mayo.edu>

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Package rviewgraph updated to version 1.4.2 with previous version 1.4.1 dated 2021-05-12

Title: Animated Graph Layout Viewer
Description: Provides 'Java' graphical user interfaces for viewing, manipulating and plotting graphs. Graphs may be directed or undirected.
Author: Alun Thomas
Maintainer: Alun Thomas <Alun.Thomas@utah.edu>

Diff between rviewgraph versions 1.4.1 dated 2021-05-12 and 1.4.2 dated 2023-05-10

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Package AirMonitor updated to version 0.3.11 with previous version 0.3.9 dated 2023-02-05

Title: Air Quality Data Analysis
Description: Utilities for working with hourly air quality monitoring data with a focus on small particulates (PM2.5). A compact data model is structured as a list with two dataframes. A 'meta' dataframe contains spatial and measuring device metadata associated with deployments at known locations. A 'data' dataframe contains a 'datetime' column followed by columns of measurements associated with each "device-deployment". Algorithms to calculate NowCast and the associated Air Quality Index (AQI) are defined at the US Environmental Projection Agency AirNow program: <https://www.airnow.gov/sites/default/files/2020-05/aqi-technical-assistance-document-sept2018.pdf>.
Author: Jonathan Callahan [aut, cre], Spencer Pease [ctb], Hans Martin [ctb], Rex Thompson [ctb]
Maintainer: Jonathan Callahan <jonathan.s.callahan@gmail.com>

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Package Peptides updated to version 2.4.5 with previous version 2.4.4 dated 2021-05-14

Title: Calculate Indices and Theoretical Physicochemical Properties of Protein Sequences
Description: Includes functions to calculate several physicochemical properties and indices for amino-acid sequences as well as to read and plot 'XVG' output files from the 'GROMACS' molecular dynamics package.
Author: Daniel Osorio [aut, cre] , Paola Rondon-Villarreal [aut, ths] , Rodrigo Torres [aut, ths] , J. Sebastian Paez [ctb] , Luis Pedro Coelho [ctb] , Richel J.C. Bilderbeek [ctb] , Florian C. Sigloch [ctb]
Maintainer: Daniel Osorio <daniecos@uio.no>

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New package nmrrr with initial version 1.0.0
Package: nmrrr
Title: Binning and Visualizing NMR Spectra in Environmental Samples
Version: 1.0.0
Description: A reproducible workflow for binning and visualizing NMR (nuclear magnetic resonance) spectra from environmental samples. The 'nmrrr' package is intended for post-processing of NMR data, including importing, merging and, cleaning data from multiple files, visualizing NMR spectra, performing binning/integrations for compound classes, and relative abundance calculations. This package can be easily inserted into existing analysis workflows by users to help with analyzing and interpreting NMR data.
URL: https://github.com/kaizadp/nmrrr
BugReports: https://github.com/kaizadp/nmrrr/issues
License: MIT + file LICENSE
Copyright: Battelle Memorial Institute
Encoding: UTF-8
Imports: DescTools, ggplot2, tidyr, utils
Suggests: covr, knitr, rmarkdown, testthat (>= 3.0.0), tibble
Depends: R (>= 3.50)
LazyData: true
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2023-05-09 17:27:00 UTC; pate212
Author: Kaizad Patel [aut, cre] , Allison Myers-Pigg [aut] , Ben Bond-Lamberty [ctb] , Morgan Barnes [ctb]
Maintainer: Kaizad Patel <kaizad.patel@pnnl.gov>
Repository: CRAN
Date/Publication: 2023-05-10 16:10:02 UTC

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New package modACDC with initial version 1.0.0
Package: modACDC
Title: Association of Covariance for Detecting Differential Co-Expression
Version: 1.0.0
Maintainer: Katelyn Queen <kjqueen@usc.edu>
Description: A series of functions to implement association of covariance for detecting differential co-expression (ACDC), a novel approach for detection of differential co-expression that simultaneously accommodates multiple phenotypes or exposures with binary, ordinal, or continuous data types. Users can use the default method which identifies modules by Partition or may supply their own modules. Also included are functions to choose an information loss criterion (ILC) for Partition using OmicS-data-based Complex trait Analysis (OSCA). The manuscript describing these methods is as follows: Queen K, Nguyen MN, Gilliland F, Chun S, Raby BA, Millstein J. "ACDC: a general approach for detecting phenotype or exposure associated co-expression" (2023) <https://www.frontiersin.org/articles/10.3389/fmed.2023.1118824/abstract>.
License: MIT + file LICENSE
URL: https://github.com/USCbiostats/ACDC
Depends: R (>= 4.1.0)
Imports: CCA, CCP, data.table, foreach, ggplot2, partition, doParallel, parallel, utils, stats, tidyr
Encoding: UTF-8
NeedsCompilation: no
Packaged: 2023-05-09 17:44:14 UTC; katelynqueen
Author: Katelyn Queen [aut, cre, cph] , Joshua Millstein [aut, cph]
Repository: CRAN
Date/Publication: 2023-05-10 16:10:06 UTC

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Package dynamite updated to version 1.4.1 with previous version 1.3.3 dated 2023-04-18

Title: Bayesian Modeling and Causal Inference for Multivariate Longitudinal Data
Description: Easy-to-use and efficient interface for Bayesian inference of complex panel (time series) data using dynamic multivariate panel models by Helske and Tikka (2022) <doi:10.31235/osf.io/mdwu5>. The package supports joint modeling of multiple measurements per individual, time-varying and time-invariant effects, and a wide range of discrete and continuous distributions. Estimation of these dynamic multivariate panel models is carried out via 'Stan'. For an in-depth tutorial of the package, see (Tikka and Helske, 2023) <arxiv:2302.01607>.
Author: Santtu Tikka [aut, cre] , Jouni Helske [aut] , Nicholas Clark [rev], Lucy D’Agostino McGowan [rev]
Maintainer: Santtu Tikka <santtuth@gmail.com>

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New package DataSetsUni with initial version 0.1
Package: DataSetsUni
Title: A Collection of Univariate Data Sets
Version: 0.1
Date: 2023-05-10
Author: Muhammad Imran [aut, cre], M.H Tahir [ctb], Farrukh Jamal [ctb]
Maintainer: Muhammad Imran <imranshakoor84@yahoo.com>
Depends: R (>= 3.5)
Description: A collection of widely used univariate data sets of various applied domains on applications of distribution theory. The functions allow researchers and practitioners to quickly, easily, and efficiently access and use these data sets. The data are related to different applied domains and as follows: Bio-medical, survival analysis, medicine, reliability analysis, hydrology, actuarial science, operational research, meteorology, extreme values, quality control, engineering, finance, sports and economics. The total 100 data sets are documented along with associated references for further details and uses.
License: GPL (>= 2)
Encoding: UTF-8
NeedsCompilation: no
Packaged: 2023-05-10 06:20:24 UTC; Amir computers
Repository: CRAN
Date/Publication: 2023-05-10 16:20:02 UTC

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Package D3mirt updated to version 1.0.2 with previous version 1.0.1 dated 2023-04-28

Title: Descriptive 3D Multidimensional Item Response Theory Modeling
Description: The 'D3mirt' package is used for identifying, estimating, and plotting descriptive multidimensional item response theory models, restricted to 3D and dichotomous or polytomous data that fit the two-parameter logistic model or the graded response model. The method is foremost explorative and centered around the plot function that exposes item characteristics and constructs, represented by vector arrows, located in a three-dimensional interactive space. The results can be useful for item-level analysis as well as test development.
Author: Erik Forsberg [aut, cre, cph]
Maintainer: Erik Forsberg <forsbergpsychometrics@gmail.com>

Diff between D3mirt versions 1.0.1 dated 2023-04-28 and 1.0.2 dated 2023-05-10

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New package vatcheckapi with initial version 0.1.0
Package: vatcheckapi
Title: Client for the 'vatcheckapi.com' VAT Validation API
Version: 0.1.0
Description: An R client for the 'vatcheckapi.com' VAT number validation API. The API requires registration of an API key. Basic features are free, some require a paid subscription. You can find the full API documentation at <https://vatcheckapi.com/docs> .
License: MIT + file LICENSE
Encoding: UTF-8
URL: https://vatcheckapi.com, https://vatcheckapi.com/docs
Imports: httr, jsonlite
Suggests: knitr, rmarkdown, testthat (>= 3.0.0)
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2023-05-09 16:47:45 UTC; andreasaltheimer
Author: Dominik Kukacka [aut, cre]
Maintainer: Dominik Kukacka <dominik@everapi.com>
Repository: CRAN
Date/Publication: 2023-05-10 16:00:02 UTC

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Package nlsr updated to version 2023.5.8 with previous version 2023.2.12 dated 2023-02-14

Title: Functions for Nonlinear Least Squares Solutions - Updated 2022
Description: Provides tools for working with nonlinear least squares problems. For the estimation of models reliable and robust tools than nls(), where the the Gauss-Newton method frequently stops with 'singular gradient' messages. This is accomplished by using, where possible, analytic derivatives to compute the matrix of derivatives and a stabilization of the solution of the estimation equations. Tools for approximate or externally supplied derivative matrices are included. Bounds and masks on parameters are handled properly.
Author: John C Nash [aut, cre], Duncan Murdoch [aut], Fernando Miguez [ctb], Arkajyoti Bhattacharjee [ctb]
Maintainer: John C Nash <nashjc@uottawa.ca>

Diff between nlsr versions 2023.2.12 dated 2023-02-14 and 2023.5.8 dated 2023-05-10

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New package ggtricks with initial version 0.1.0
Package: ggtricks
Title: Create Sector and Other Charts Easily Using Grammar of Graphics
Version: 0.1.0
Description: A collection of several geoms to create graphics, using 'ggplot2' and the Cartesian coordinate system. You use the familiar mapping 'Grammar of Graphics' without the need to do another transformation into polar coordinates.
License: MIT + file LICENSE
URL: https://github.com/AbdoulMa/ggtricks, https://abdoulma.github.io/ggtricks/
BugReports: https://github.com/AbdoulMa/ggtricks/issues
Imports: cli, ggplot2
Suggests: covr, rmarkdown, testthat (>= 3.0.0)
Encoding: UTF-8
NeedsCompilation: no
Packaged: 2023-05-09 16:42:23 UTC; abdoul-ma
Author: Abdoul ISSA BIDA [aut, cre]
Maintainer: Abdoul ISSA BIDA <contact@abdoulblog.com>
Repository: CRAN
Date/Publication: 2023-05-10 16:00:05 UTC

More information about ggtricks at CRAN
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New package rusquant with initial version 1.0.1
Package: rusquant
Title: Quantitative Trading Framework
Version: 1.0.1
Date: 2023-05-08
Author: Vyacheslav Arbuzov[cph, cre, aut], Sergey Edunov[aut]
Depends: quantmod,data.table,jsonlite,httr,xts
Imports: XML,stringr,jose,stats,rvest
Maintainer: Vyacheslav Arbuzov <arbuzov1989@gmail.com>
Description: Collection of functions to retrieve financial data from various sources, including brokerage and exchange platforms, financial websites, and data providers. Includes functions to retrieve account information, portfolio information, and place/cancel orders from different brokers. Additionally, allows users to download historical data such as earnings, dividends, stock splits.
LazyLoad: yes
License: GPL-3
Encoding: UTF-8
URL: https://rusquant.ru,https://docs.rusquant.ru
BugReports: https://github.com/arbuzovv/rusquant/issues
NeedsCompilation: no
Packaged: 2023-05-09 13:42:50 UTC; vyacheslav
Repository: CRAN
Date/Publication: 2023-05-10 13:50:02 UTC

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New package ResIN with initial version 0.1.0
Package: ResIN
Title: Response Item Networks ('ResIN')
Version: 0.1.0
Maintainer: Philip Warncke <pwarncke@live.unc.edu>
Description: Contains various tools to perform and visualize Response Item Networks ('ResIN's'). 'ResIN' binarizes ordered-categorical and qualitative response choices from (survey) data, calculates pairwise associations and maps the location of each item response as a node in a force-directed network. Please refer to <https://www.resinmethod.net/> for more details.
License: GPL-3
URL: https://github.com/pwarncke77/ResIN
BugReports: https://github.com/pwarncke77/ResIN/issues
Depends: R (>= 4.1.0)
Imports: ggplot2 (>= 3.4.2), dplyr (>= 1.0.0), fastDummies (>= 1.6.3), qgraph (>= 1.9.4), igraph (>= 1.4.2), wCorr (>= 1.9.6), Matrix, DirectedClustering (>= 0.1.1)
Encoding: UTF-8
LazyData: true
Suggests: knitr, rmarkdown
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2023-05-09 14:21:59 UTC; philip
Author: Philip Warncke [cre, aut], Dino Carpentras [aut]
Repository: CRAN
Date/Publication: 2023-05-10 13:50:06 UTC

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New package freecurrencyapi with initial version 0.1.0
Package: freecurrencyapi
Title: Client for the 'freecurrencyapi.com' Currency Conversion API
Version: 0.1.0
Description: An R client for the 'freecurrencyapi.com' currency conversion API. The API requires registration of an API key. You can find the full API documentation at <https://freecurrencyapi.com/docs> .
License: MIT + file LICENSE
Encoding: UTF-8
URL: https://freecurrencyapi.com, https://freecurrencyapi.com/docs
Imports: httr, jsonlite
Suggests: knitr, rmarkdown, testthat (>= 3.0.0)
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2023-05-09 09:22:10 UTC; andreasaltheimer
Author: Dominik Kukacka [aut, cre]
Maintainer: Dominik Kukacka <dominik@everapi.com>
Repository: CRAN
Date/Publication: 2023-05-10 13:40:02 UTC

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Package DatabaseConnector updated to version 6.2.1 with previous version 6.2.0 dated 2023-04-13

Title: Connecting to Various Database Platforms
Description: An R 'DataBase Interface' ('DBI') compatible interface to various database platforms ('PostgreSQL', 'Oracle', 'Microsoft SQL Server', 'Amazon Redshift', 'Microsoft Parallel Database Warehouse', 'IBM Netezza', 'Apache Impala', 'Google BigQuery', 'Snowflake', 'Spark', and 'SQLite'). Also includes support for fetching data as 'Andromeda' objects. Uses either 'Java Database Connectivity' ('JDBC') or other 'DBI' drivers to connect to databases.
Author: Martijn Schuemie [aut, cre], Marc Suchard [aut], Observational Health Data Science and Informatics [cph], Microsoft Inc. [cph] , PostgreSQL Global Development Group [cph] , Oracle Inc. [cph] , Amazon Inc. [cph]
Maintainer: Martijn Schuemie <schuemie@ohdsi.org>

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More information about DatabaseConnector at CRAN
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Package cyclotomic updated to version 1.1.0 with previous version 1.0.0 dated 2023-04-18

Title: The Field of Cyclotomic Numbers
Description: The cyclotomic numbers are complex numbers that can be thought of as the rational numbers extended with the roots of unity. They are represented exactly, enabling exact computations. They contain the Gaussian rationals (complex numbers with rational real and imaginary parts) as well as the square roots of all rational numbers. They also contain the sine and cosine of all rational multiples of pi. The algorithms implemented in this package are taken from the 'Haskell' package 'cyclotomic', whose algorithms are adapted from code by Martin Schoenert and Thomas Breuer in the 'GAP' project (<https://www.gap-system.org/>). Cyclotomic numbers have applications in number theory, algebraic geometry, algebraic number theory, coding theory, and in the theory of graphs and combinatorics. They have connections to the theory of modular functions and modular curves.
Author: Stephane Laurent [aut, cre], Scott N. Walck [cph]
Maintainer: Stephane Laurent <laurent_step@outlook.fr>

Diff between cyclotomic versions 1.0.0 dated 2023-04-18 and 1.1.0 dated 2023-05-10

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More information about cyclotomic at CRAN
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Package parquetize updated to version 0.5.6.1 with previous version 0.5.5 dated 2023-03-28

Title: Convert Files to Parquet Format
Description: Collection of functions to get files in parquet format. Parquet is a columnar storage file format <https://parquet.apache.org/>. The files to convert can be of several formats ("csv", "RData", "rds", "RSQLite", "json", "ndjson", "SAS", "SPSS"...).
Author: Damien Dotta [aut, cre], Nicolas Chuche [aut]
Maintainer: Damien Dotta <damien.dotta@live.fr>

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More information about parquetize at CRAN
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Package daterangepicker updated to version 0.2.0 with previous version 0.1.0 dated 2020-03-20

Title: Create a Shiny Date-Range Input
Description: A Shiny Input for date-ranges, which pops up two calendars for selecting dates, times, or predefined ranges like "Last 30 Days". It wraps the JavaScript library 'daterangepicker' which is available at <https://www.daterangepicker.com>.
Author: Sebastian Gatscha [aut, cre]
Maintainer: Sebastian Gatscha <sebastian_gatscha@gmx.at>

Diff between daterangepicker versions 0.1.0 dated 2020-03-20 and 0.2.0 dated 2023-05-10

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Package rvg updated to version 0.3.3 with previous version 0.3.2 dated 2023-01-07

Title: R Graphics Devices for 'Office' Vector Graphics Output
Description: Vector Graphics devices for 'Microsoft PowerPoint' and 'Microsoft Excel'. Functions extending package 'officer' are provided to embed 'DrawingML' graphics into 'Microsoft PowerPoint' presentations and 'Microsoft Excel' workbooks.
Author: David Gohel [aut, cre], ArData [cph], Bob Rudis [ctb] , Francois Brunetti [ctb]
Maintainer: David Gohel <david.gohel@ardata.fr>

Diff between rvg versions 0.3.2 dated 2023-01-07 and 0.3.3 dated 2023-05-10

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Package ontologics updated to version 0.7.0 with previous version 0.6.5 dated 2023-01-31

Title: Code-Logics to Handle Ontologies
Description: Provides tools to build and work with an ontology of linked (open) data in a tidy workflow. It is inspired by the Food and Agrilculture Organizations (FAO) caliper platform <https://www.fao.org/statistics/caliper/web/> and makes use of the Simple Knowledge Organisation System (SKOS).
Author: Steffen Ehrmann [aut, cre] , Arne Ruemmler [aut, ctb] , Carsten Meyer [ctb]
Maintainer: Steffen Ehrmann <steffen.ehrmann@posteo.de>

Diff between ontologics versions 0.6.5 dated 2023-01-31 and 0.7.0 dated 2023-05-10

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Package ucminf updated to version 1.1-4.2 with previous version 1.1-4.1 dated 2022-09-29

Title: General-Purpose Unconstrained Non-Linear Optimization
Description: An algorithm for general-purpose unconstrained non-linear optimization. The algorithm is of quasi-Newton type with BFGS updating of the inverse Hessian and soft line search with a trust region type monitoring of the input to the line search algorithm. The interface of 'ucminf' is designed for easy interchange with 'optim'.
Author: Hans Bruun Nielsen and Stig Bousgaard Mortensen
Maintainer: Stig Bousgaard Mortensen <stigbm@gmail.com>

Diff between ucminf versions 1.1-4.1 dated 2022-09-29 and 1.1-4.2 dated 2023-05-10

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Package pscl updated to version 1.5.5.1 with previous version 1.5.5 dated 2020-03-07

Title: Political Science Computational Laboratory
Description: Bayesian analysis of item-response theory (IRT) models, roll call analysis; computing highest density regions; maximum likelihood estimation of zero-inflated and hurdle models for count data; goodness-of-fit measures for GLMs; data sets used in writing and teaching at the Political Science Computational Laboratory; seats-votes curves.
Author: Simon Jackman, with contributions from Alex Tahk, Achim Zeileis, Christina Maimone, Jim Fearon and Zoe Meers
Maintainer: Simon Jackman <simon.jackman@sydney.edu.au>

Diff between pscl versions 1.5.5 dated 2020-03-07 and 1.5.5.1 dated 2023-05-10

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New package PRIMME with initial version 3.2-4
Package: PRIMME
Title: Eigenvalues and Singular Values and Vectors from Large Matrices
Version: 3.2-4
Date: 2023-05-9
Maintainer: Eloy Romero <eloy@cs.wm.edu>
Description: R interface to 'PRIMME' <https://www.cs.wm.edu/~andreas/software/>, a C library for computing a few eigenvalues and their corresponding eigenvectors of a real symmetric or complex Hermitian matrix, or generalized Hermitian eigenproblem. It can also compute singular values and vectors of a square or rectangular matrix. 'PRIMME' finds largest, smallest, or interior singular/eigenvalues and can use preconditioning to accelerate convergence. General description of the methods are provided in the papers Stathopoulos (2010, <doi:10.1145/1731022.1731031>) and Wu (2017, <doi:10.1137/16M1082214>). See 'citation("PRIMME")' for details.
URL: https://www.cs.wm.edu/~andreas/software/ https://github.com/primme/primme
BugReports: https://github.com/primme/primme/issues
Imports: Rcpp (>= 0.11.4)
LinkingTo: Rcpp, Matrix
Suggests: Matrix
SystemRequirements: A POSIX system. Currently Linux and OS X are known to work. GNU make.
NeedsCompilation: yes
License: GPL-3
Encoding: UTF-8
Packaged: 2023-05-09 22:36:59 UTC; eromero
Author: Eloy Romero [aut, cre], Andreas Stathopoulos [aut], Lingfei Wu [aut], College of William & Mary [cph]
Repository: CRAN
Date/Publication: 2023-05-10 08:30:02 UTC

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Package jack updated to version 5.1.0 with previous version 5.0.1 dated 2023-01-30

Title: Jack, Zonal, and Schur Polynomials
Description: Symbolic calculation and evaluation of the Jack polynomials, zonal polynomials, and Schur polynomials. Mainly based on Demmel & Koev's paper (2006) <doi:10.1090/S0025-5718-05-01780-1>. Zonal polynomials and Schur polynomials are particular cases of Jack polynomials. Zonal polynomials appear in random matrix theory. Schur polynomials appear in the field of combinatorics.
Author: Stephane Laurent
Maintainer: Stephane Laurent <laurent_step@outlook.fr>

Diff between jack versions 5.0.1 dated 2023-01-30 and 5.1.0 dated 2023-05-10

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New package qdapTools with initial version 1.3.7
Package: qdapTools
Title: Tools for the 'qdap' Package
Version: 1.3.7
Maintainer: Tyler Rinker <tyler.rinker@gmail.com>
Depends: R (>= 3.0.0)
Imports: chron, data.table (>= 1.9.6), methods, RCurl, XML
Suggests: testthat
Description: A collection of tools associated with the 'qdap' package that may be useful outside of the context of text analysis.
License: GPL-2
URL: https://github.com/trinker/qdapTools
BugReports: https://github.com/trinker/qdapTools/issues
Encoding: UTF-8
NeedsCompilation: no
Packaged: 2023-05-10 03:20:47 UTC; tylerrinker
Author: Bryan Goodrich [ctb], Dason Kurkiewicz [ctb], Kirill Muller [ctb], Tyler Rinker [aut, cre]
Repository: CRAN
Date/Publication: 2023-05-10 07:20:02 UTC

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Package pathfindR updated to version 2.0.1 with previous version 2.0.0 dated 2023-05-06

Title: Enrichment Analysis Utilizing Active Subnetworks
Description: Enrichment analysis enables researchers to uncover mechanisms underlying a phenotype. However, conventional methods for enrichment analysis do not take into account protein-protein interaction information, resulting in incomplete conclusions. pathfindR is a tool for enrichment analysis utilizing active subnetworks. The main function identifies active subnetworks in a protein-protein interaction network using a user-provided list of genes and associated p values. It then performs enrichment analyses on the identified subnetworks, identifying enriched terms (i.e. pathways or, more broadly, gene sets) that possibly underlie the phenotype of interest. pathfindR also offers functionalities to cluster the enriched terms and identify representative terms in each cluster, to score the enriched terms per sample and to visualize analysis results. The enrichment, clustering and other methods implemented in pathfindR are described in detail in Ulgen E, Ozisik O, Sezerman OU. 2019. pathfindR: An R [...truncated...]
Author: Ege Ulgen [cre, cph] , Ozan Ozisik [aut]
Maintainer: Ege Ulgen <egeulgen@gmail.com>

Diff between pathfindR versions 2.0.0 dated 2023-05-06 and 2.0.1 dated 2023-05-10

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Package nonmemica updated to version 1.0.1 with previous version 1.0.0 dated 2023-02-07

Title: Create and Evaluate NONMEM Models in a Project Context
Description: Systematically creates and modifies NONMEM(R) control streams. Harvests NONMEM output, builds run logs, creates derivative data, generates diagnostics. NONMEM (ICON Development Solutions <https://www.iconplc.com/>) is software for nonlinear mixed effects modeling. See 'package?nonmemica'.
Author: Tim Bergsma
Maintainer: Tim Bergsma <bergsmat@gmail.com>

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Package imager updated to version 0.45.2 with previous version 0.42.19 dated 2023-03-25

Title: Image Processing Library Based on 'CImg'
Description: Fast image processing for images in up to 4 dimensions (two spatial dimensions, one time/depth dimension, one colour dimension). Provides most traditional image processing tools (filtering, morphology, transformations, etc.) as well as various functions for easily analysing image data using R. The package wraps 'CImg', <http://cimg.eu>, a simple, modern C++ library for image processing.
Author: Simon Barthelme [aut], David Tschumperle [ctb], Jan Wijffels [ctb], Haz Edine Assemlal [ctb], Shota Ochi [ctb], Aaron Robotham [cre], Rodrigo Tobar [ctb]
Maintainer: Aaron Robotham <aaron.robotham@uwa.edu.au>

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Package extras updated to version 0.6.1 with previous version 0.6.0 dated 2023-04-28

Title: Helper Functions for Bayesian Analyses
Description: Functions to 'numericise' 'R' objects (coerce to numeric objects), summarise 'MCMC' (Monte Carlo Markov Chain) samples and calculate deviance residuals as well as 'R' translations of some 'BUGS' (Bayesian Using Gibbs Sampling), 'JAGS' (Just Another Gibbs Sampler), 'STAN' and 'TMB' (Template Model Builder) functions.
Author: Joe Thorley [aut, cre] , Nicole Hill [aut] , Kirill Mueller [ctb] , Nadine Hussein [ctb] , Poisson Consulting [cph, fnd]
Maintainer: Joe Thorley <joe@poissonconsulting.ca>

Diff between extras versions 0.6.0 dated 2023-04-28 and 0.6.1 dated 2023-05-10

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Permanent link

Package DCD (with last version 0.1.0) was removed from CRAN

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

2017-09-12 0.1.0

Permanent link
Package penDvine (with last version 0.2.4) was removed from CRAN

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

2015-07-09 0.2.4
2013-03-12 0.2.2
2012-07-23 0.2
2012-07-16 0.1

Permanent link
Package contingencytables updated to version 2.0.0 with previous version 1.0.4 dated 2022-12-12

Title: Statistical Analysis of Contingency Tables
Description: Provides functions to perform statistical inference of data organized in contingency tables. This package is a companion to the "Statistical Analysis of Contingency Tables" book by Fagerland et al. <ISBN 9781466588172>.
Author: Morten Wang Fagerland [aut], Stian Lydersen [ctb], Petter Laake [ctb], Waldir Leoncio [cre], Ole Christian Lingjaerde [trl]
Maintainer: Waldir Leoncio <w.l.netto@medisin.uio.no>

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 NAMESPACE                                                   |   30 
 NEWS.md                                                     |only
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 R/Adjusted_inv_sinh_CI_ratio_2x2.R                          |   49 
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 R/AgrestiCaffo_CI_2x2.R                                     |   36 
 R/AgrestiCoull_CI_1x2.R                                     |   40 
 R/Arcsine_CI_1x2.R                                          |   44 
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 R/BaptistaPike_midP_CI_2x2.R                                |   40 
 R/Bhapkar_test_paired_cxc.R                                 |   52 
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 R/Blaker_exact_test_1x2.R                                   |   35 
 R/Blaker_midP_CI_1x2.R                                      |   41 
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 R/Bonferroni_type_CIs_paired_cxc.R                          |   35 
 R/Bonferroni_type_CIs_rxc.R                                 |   27 
 R/Brant_test_2xc.R                                          |   35 
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 R/Chacko_test_1xc.R                                         |   32 
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 R/Exact_unconditional_test_2x2.R                            |   51 
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 R/Fisher_midP_test_2x2.R                                    |   49 
 R/FleissEveritt_test_paired_cxc.R                           |   41 
 R/FleissLevinPaik_test_paired_cxc.R                         |   41 
 R/Gart_adjusted_logit_CI_2x2.R                              |   31 
 R/Gold_Wald_CIs_1xc.R                                       |   30 
 R/Goodman_Wald_CIs_1xc.R                                    |   30 
 R/Goodman_Wald_CIs_for_diffs_1xc.R                          |   58 
 R/Goodman_Wilson_score_CIs_1xc.R                            |   33 
 R/Independence_smoothed_logit_CI_2x2.R                      |   33 
 R/Inv_sinh_CI_OR_2x2.R                                      |   33 
 R/Inv_sinh_CI_ratio_2x2.R                                   |   29 
 R/InverseVariance_estimate_stratified_2x2.R                 |   42 
 R/Jeffreys_CI_1x2.R                                         |   35 
 R/JonckheereTerpstra_test_rxc.R                             |   42 
 R/Katz_log_CI_2x2.R                                         |   35 
 R/Kendalls_tau_b_rxc.R                                      |   48 
 R/Kendalls_tau_b_rxc_bca.R                                  |   50 
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 R/LR_CI_1x2.R                                               |   35 
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 R/Mee_asymptotic_score_CI_2x2.R                             |   29 
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 R/Pearson_LR_tests_rxc.R                                    |   55 
 R/Pearson_LR_tests_unspecific_ordering_rx2.R                |   29 
 R/Pearson_chi_squared_test_1xc.R                            |   26 
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 R/Pearson_correlation_coefficient_rxc.R                     |   51 
 R/Pearson_correlation_coefficient_rxc_bca.R                 |   54 
 R/Pearson_residuals_rxc.R                                   |   47 
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 R/PriceBonett_approximate_Bayes_CI_2x2.R                    |   32 
 R/QuesenberryHurst_Wilson_score_CIs_1xc.R                   |   33 
 R/RBG_test_and_CI_stratified_2x2.R                          |   45 
 R/Scheffe_type_CIs_paired_cxc.R                             |   30 
 R/Scheffe_type_CIs_rxc.R                                    |   27 
 R/Score_test_1x2.R                                          |   33 
 R/Score_test_CC_1x2.R                                       |   36 
 R/Score_test_and_CI_marginal_mean_scores_paired_cxc.R       |   36 
 R/Score_test_for_effect_in_the_probit_model_2xc.R           |   28 
 R/Spearman_correlation_coefficient_rxc.R                    |   49 
 R/Spearman_correlation_coefficient_rxc_bca.R                |   51 
 R/Stuart_test_paired_cxc.R                                  |   51 
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 R/Transformed_Wilson_score_CI_paired_2x2.R                  |   43 
 R/Trend_estimate_CI_tests_rx2.R                             |   62 -
 R/Uncorrected_asymptotic_score_CI_2x2.R                     |   40 
 R/Wald_CI_1x2.R                                             |   38 
 R/Wald_CI_2x2.R                                             |   32 
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 R/Wald_CI_BonettPrice_paired_2x2.R                          |   44 
 R/Wald_CI_CC_1x2.R                                          |   35 
 R/Wald_CI_CC_2x2.R                                          |   34 
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 R/Wald_CI_OR_paired_2x2.R                                   |   33 
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 R/the_paired_cxc_table_nominal.R                            |   58 
 R/the_paired_cxc_table_ordinal.R                            |   74 -
 R/the_rx2_table.R                                           |  121 --
 R/the_rxc_table.R                                           |  211 +--
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 man/AgrestiCaffo_CI_2x2.Rd                                  |   14 
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 man/BaptistaPike_exact_conditional_CI_2x2.Rd                |   26 
 man/BaptistaPike_midP_CI_2x2.Rd                             |   20 
 man/Bhapkar_test_paired_cxc.Rd                              |   12 
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 man/Blaker_exact_test_1x2.Rd                                |   24 
 man/Blaker_midP_CI_1x2.Rd                                   |   24 
 man/Blaker_midP_test_1x2.Rd                                 |   24 
 man/BonettPrice_hybrid_Wilson_score_CI_CC_paired_2x2.Rd     |   22 
 man/BonettPrice_hybrid_Wilson_score_CI_paired_2x2.Rd        |   19 
 man/Bonferroni_type_CIs_paired_cxc.Rd                       |   12 
 man/Bonferroni_type_CIs_rxc.Rd                              |   12 
 man/Brant_test_2xc.Rd                                       |   18 
 man/BreslowDay_homogeneity_test_stratified_2x2.Rd           |   26 
 man/Chacko_test_1xc.Rd                                      |   12 
 man/ClopperPearson_exact_CI_1x2.Rd                          |   24 
 man/ClopperPearson_exact_CI_1x2_beta_version.Rd             |   28 
 man/ClopperPearson_midP_CI_1x2.Rd                           |   24 
 man/CochranArmitage_CI_rx2.Rd                               |   20 
 man/CochranArmitage_MH_tests_rx2.Rd                         |   21 
 man/CochranArmitage_exact_cond_midP_tests_rx2.Rd            |   20 
 man/CochranMantelHaenszel_test_stratified_2x2.Rd            |   26 
 man/Cochran_Q_test_stratified_2x2.Rd                        |   31 
 man/Cornfield_exact_conditional_CI_2x2.Rd                   |   20 
 man/Cornfield_midP_CI_2x2.Rd                                |   20 
 man/Cumulative_models_for_2xc.Rd                            |   25 
 man/Cumulative_models_for_rxc.Rd                            |   27 
 man/Exact_binomial_test_1x2.Rd                              |   25 
 man/Exact_cond_midP_linear_rank_tests_2xc.Rd                |   20 
 man/Exact_cond_midP_tests_rxc.Rd                            |   16 
 man/Exact_cond_midP_unspecific_ordering_rx2.Rd              |   17 
 man/Exact_multinomial_test_1xc.Rd                           |   15 
 man/Exact_unconditional_test_2x2.Rd                         |   25 
 man/FisherFreemanHalton_asymptotic_test_rxc.Rd              |   13 
 man/Fisher_exact_test_2x2.Rd                                |   20 
 man/Fisher_midP_test_2x2.Rd                                 |   20 
 man/FleissEveritt_test_paired_cxc.Rd                        |   12 
 man/FleissLevinPaik_test_paired_cxc.Rd                      |   12 
 man/Gart_adjusted_logit_CI_2x2.Rd                           |   16 
 man/Gold_Wald_CIs_1xc.Rd                                    |   11 
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 man/Goodman_Wald_CIs_for_diffs_1xc.Rd                       |   16 
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 man/Independence_smoothed_logit_CI_2x2.Rd                   |   16 
 man/Inv_sinh_CI_OR_2x2.Rd                                   |   16 
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 man/InverseVariance_estimate_stratified_2x2.Rd              |   26 
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 man/JonckheereTerpstra_test_rxc.Rd                          |   30 
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 man/Koopman_asymptotic_score_CI_2x2.Rd                      |   16 
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 man/ML_estimates_and_CIs_stratified_2x2.Rd                  |   27 
 man/MOVER_R_Wilson_CI_OR_2x2.Rd                             |   14 
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 man/MOVER_Wilson_score_CI_paired_2x2.Rd                     |   17 
 man/MantelHaenszel_estimate_stratified_2x2.Rd               |   26 
 man/MantelHaenszel_test_2xc.Rd                              |   13 
 man/McNemarBowker_test_paired_cxc.Rd                        |   11 
 man/McNemar_asymptotic_test_CC_paired_2x2.Rd                |   24 
 man/McNemar_asymptotic_test_paired_2x2.Rd                   |   25 
 man/McNemar_exact_cond_test_paired_2x2.Rd                   |   25 
 man/McNemar_exact_unconditional_test_paired_2x2.Rd          |   30 
 man/McNemar_midP_test_paired_2x2.Rd                         |   24 
 man/Mee_asymptotic_score_CI_2x2.Rd                          |   15 
 man/MidP_binomial_test_1x2.Rd                               |   18 
 man/MidP_multinomial_test_1xc.Rd                            |   15 
 man/MiettinenNurminen_asymptotic_score_CI_OR_2x2.Rd         |   21 
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 man/MiettinenNurminen_asymptotic_score_CI_ratio_2x2.Rd      |   16 
 man/Newcombe_hybrid_score_CI_2x2.Rd                         |   14 
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 man/Pearson_LR_test_common_effect_stratified_2x2.Rd         |   26 
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 man/Pearson_LR_tests_unspecific_ordering_rx2.Rd             |   20 
 man/Pearson_chi_squared_test_1xc.Rd                         |   12 
 man/Pearson_chi_squared_test_2x2.Rd                         |   20 
 man/Pearson_chi_squared_test_CC_2x2.Rd                      |   20 
 man/Pearson_correlation_coefficient_rxc.Rd                  |   33 
 man/Pearson_correlation_coefficient_rxc_bca.Rd              |   32 
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 man/Peto_OR_estimate_stratified_2x2.Rd                      |   22 
 man/Peto_homogeneity_test_stratified_2x2.Rd                 |   21 
 man/PriceBonett_approximate_Bayes_CI_2x2.Rd                 |   20 
 man/QuesenberryHurst_Wilson_score_CIs_1xc.Rd                |   10 
 man/RBG_test_and_CI_stratified_2x2.Rd                       |   25 
 man/Scheffe_type_CIs_paired_cxc.Rd                          |   11 
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 man/Score_test_1x2.Rd                                       |   18 
 man/Score_test_CC_1x2.Rd                                    |   18 
 man/Score_test_and_CI_marginal_mean_scores_paired_cxc.Rd    |   22 
 man/Score_test_for_effect_in_the_probit_model_2xc.Rd        |   18 
 man/Spearman_correlation_coefficient_rxc.Rd                 |   32 
 man/Spearman_correlation_coefficient_rxc_bca.Rd             |   36 
 man/Stuart_test_paired_cxc.Rd                               |   11 
 man/Tang_asymptotic_score_CI_paired_2x2.Rd                  |   14 
 man/Tango_asymptotic_score_CI_paired_2x2.Rd                 |   14 
 man/Transformed_Blaker_exact_CI_paired_2x2.Rd               |   14 
 man/Transformed_Clopper_Pearson_exact_CI_paired_2x2.Rd      |   24 
 man/Transformed_Clopper_Pearson_midP_CI_paired_2x2.Rd       |   24 
 man/Transformed_Wilson_score_CI_paired_2x2.Rd               |   20 
 man/Trend_estimate_CI_tests_rx2.Rd                          |   27 
 man/Uncorrected_asymptotic_score_CI_2x2.Rd                  |   23 
 man/Wald_CI_1x2.Rd                                          |   22 
 man/Wald_CI_2x2.Rd                                          |   15 
 man/Wald_CI_AgrestiMin_paired_2x2.Rd                        |   23 
 man/Wald_CI_BonettPrice_paired_2x2.Rd                       |   23 
 man/Wald_CI_CC_1x2.Rd                                       |   18 
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 man/the_1xc_table_tests.Rd                                  |    6 
 man/the_2x2_table_CIs_OR.Rd                                 |   16 
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 man/the_2x2_table_CIs_ratio.Rd                              |   10 
 man/the_2x2_table_tests.Rd                                  |   16 
 man/the_2xc_table.Rd                                        |    9 
 man/the_paired_2x2_table_CIs_OR.Rd                          |    8 
 man/the_paired_2x2_table_CIs_difference.Rd                  |    8 
 man/the_paired_2x2_table_CIs_ratio.Rd                       |    8 
 man/the_paired_2x2_table_tests.Rd                           |   20 
 man/the_paired_cxc_table_nominal.Rd                         |    5 
 man/the_paired_cxc_table_ordinal.Rd                         |   13 
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 379 files changed, 5396 insertions(+), 7141 deletions(-)

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