Fri, 17 May 2024

Package nasapower updated to version 4.2.1 with previous version 4.2.0 dated 2024-02-02

Title: NASA POWER API Client
Description: An API client for NASA POWER global meteorology, surface solar energy and climatology data API. POWER (Prediction Of Worldwide Energy Resources) data are freely available for download with varying spatial resolutions dependent on the original data and with several temporal resolutions depending on the POWER parameter and community. This work is funded through the NASA Earth Science Directorate Applied Science Program. For more on the data themselves, the methodologies used in creating, a web- based data viewer and web access, please see <https://power.larc.nasa.gov/>.
Author: Adam H. Sparks [aut, cre] , Scott Chamberlain [rev] , Hazel Kavili [rev] , Alison Boyer [rev] , Fernando Miguez [ctb] , Maelle Salmon [ctb] , Phillip D. Alderman [ctb] ` must use `I` for literal data as of vroom 1.5.0.', see <https://github.com/ropen [...truncated...]
Maintainer: Adam H. Sparks <adamhsparks@gmail.com>

Diff between nasapower versions 4.2.0 dated 2024-02-02 and 4.2.1 dated 2024-05-17

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Package formods updated to version 0.1.5 with previous version 0.1.4 dated 2024-04-03

Title: 'Shiny' Modules for General Tasks
Description: 'Shiny' apps can often make use of the same key elements, this package provides modules for common tasks (data upload, wrangling data, figure generation and saving the app state). These modules can react and interact as well as generate code to create reproducible analyses.
Author: John Harrold [aut, cre]
Maintainer: John Harrold <john.m.harrold@gmail.com>

Diff between formods versions 0.1.4 dated 2024-04-03 and 0.1.5 dated 2024-05-17

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Package tinytable updated to version 0.3.0 with previous version 0.2.1 dated 2024-03-28

Title: Simple and Configurable Tables in 'HTML', 'LaTeX', 'Markdown', 'Word', 'PNG', 'PDF', and 'Typst' Formats
Description: Create highly customized tables with this simple and dependency-free package. Data frames can be converted to 'HTML', 'LaTeX', 'Markdown', 'Word', 'PNG', 'PDF', or 'Typst' tables. The user interface is minimalist and easy to learn. The syntax is concise. 'HTML' tables can be customized using the flexible 'Bootstrap' framework, and 'LaTeX' code with the 'tabularray' package.
Author: Vincent Arel-Bundock [aut, cre]
Maintainer: Vincent Arel-Bundock <vincent.arel-bundock@umontreal.ca>

Diff between tinytable versions 0.2.1 dated 2024-03-28 and 0.3.0 dated 2024-05-17

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New package HydroMe with initial version 2.1.1
Package: HydroMe
Title: Estimating Water Retention and Infiltration Model Parameters using Experimental Data
Version: 2.1.1
Description: Contains functions for estimating the parameters of infiltration and water retention models using the curve-fitting methods as discussed in Omuto and Gumbe (2009) ("Estimating water infiltration and retention characteristics using a computer program in R"<doi:10.1016/j.cageo.2008.08.011>). The models considered are those that are commonly used in soil science. Version 2 of the package has new models for water retention characteristic curves.
License: GPL (>= 3.5.0)
Encoding: UTF-8
LazyData: true
Imports: stats
Suggests: minpack.lm, nlme
NeedsCompilation: no
Packaged: 2024-05-17 18:08:38 UTC; Cthine
Author: Christian Thine Omuto [aut, cre]
Maintainer: Christian Thine Omuto <thineomuto@yahoo.com>
Repository: CRAN
Date/Publication: 2024-05-18 00:10:02 UTC

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Package fastbeta updated to version 0.3.0 with previous version 0.2.0 dated 2023-12-11

Title: Fast Approximation of Time-Varying Infectious Disease Transmission Rates
Description: A fast method for approximating time-varying infectious disease transmission rates from disease incidence time series and other data, based on a discrete time approximation of an SEIR model, as analyzed in Jagan et al. (2020) <doi:10.1371/journal.pcbi.1008124>.
Author: Mikael Jagan [aut, cre]
Maintainer: Mikael Jagan <jaganmn@mcmaster.ca>

Diff between fastbeta versions 0.2.0 dated 2023-12-11 and 0.3.0 dated 2024-05-17

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Package traits updated to version 0.5.1 with previous version 0.5.0 dated 2020-08-27

Title: Species Trait Data from Around the Web
Description: Species trait data from many different sources, including sequence data from 'NCBI' (<https://www.ncbi.nlm.nih.gov/>), plant trait data from 'BETYdb', data from 'EOL' 'Traitbank', 'Birdlife' International, and more.
Author: David LeBauer [aut, cre] , Scott Chamberlain [aut] , Zachary Foster [aut], Ignasi Bartomeus [aut], Chris Black [aut], David Harris [aut], Rupert Collins [ctb]
Maintainer: David LeBauer <dlebauer@gmail.com>

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Package TCIU updated to version 1.2.6 with previous version 1.2.5 dated 2024-03-08

Title: Spacekime Analytics, Time Complexity and Inferential Uncertainty
Description: Provide the core functionality to transform longitudinal data to complex-time (kime) data using analytic and numerical techniques, visualize the original time-series and reconstructed kime-surfaces, perform model based (e.g., tensor-linear regression) and model-free classification and clustering methods in the book Dinov, ID and Velev, MV. (2021) "Data Science: Time Complexity, Inferential Uncertainty, and Spacekime Analytics", De Gruyter STEM Series, ISBN 978-3-11-069780-3. <https://www.degruyter.com/view/title/576646>. The package includes 18 core functions which can be separated into three groups. 1) draw longitudinal data, such as Functional magnetic resonance imaging(fMRI) time-series, and forecast or transform the time-series data. 2) simulate real-valued time-series data, e.g., fMRI time-courses, detect the activated areas, report the corresponding p-values, and visualize the p-values in the 3D brain space. 3) Laplace transform and kimesurface reconstructions of the fMRI d [...truncated...]
Author: Yongkai Qiu [aut], Zhe Yin [aut], Jinwen Cao [aut], Yupeng Zhang [aut], Yuyao Liu [aut], Rongqian Zhang [aut], Yueyang Shen [aut, cre], Rouben Rostamian [ctb], Ranjan Maitra [ctb], Daniel Rowe [ctb], Daniel Adrian [ctb] , Yunjie Guo [aut], Ivo Dinov [...truncated...]
Maintainer: Yueyang Shen <petersyy@umich.edu>

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Package sievePH updated to version 1.1 with previous version 1.0.4 dated 2023-02-03

Title: Sieve Analysis Methods for Proportional Hazards Models
Description: Implements a suite of semiparametric and nonparametric kernel-smoothed estimation and testing procedures for continuous mark-specific stratified hazard ratio (treatment/placebo) models in a randomized treatment efficacy trial with a time-to-event endpoint. Semiparametric methods, allowing multivariate marks, are described in Juraska M and Gilbert PB (2013), Mark-specific hazard ratio model with multivariate continuous marks: an application to vaccine efficacy. Biometrics 69(2):328-337 <doi:10.1111/biom.12016>, and in Juraska M and Gilbert PB (2016), Mark-specific hazard ratio model with missing multivariate marks. Lifetime Data Analysis 22(4):606-25 <doi:10.1007/s10985-015-9353-9>. Nonparametric kernel-smoothed methods, allowing univariate marks only, are described in Sun Y and Gilbert PB (2012), Estimation of stratified mark‐specific proportional hazards models with missing marks. Scandinavian Journal of Statistics}, 39(1):34-52 <doi:10.1111/j.1467-9469.2011.00746.x> [...truncated...]
Author: Michal Juraska [aut, cre], Li Li [ctb], Stephanie Wu [ctb]
Maintainer: Michal Juraska <mjuraska@fredhutch.org>

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New package seqmon with initial version 2.5
Package: seqmon
Title: Group Sequential Design Class for Clinical Trials
Version: 2.5
Date: 2024-05-06
Author: David A Schoenfeld and Hui Zheng
Maintainer: Hui Zheng <hzheng1@mgh.harvard.edu>
Description: S4 class object for creating and managing group sequential designs. It calculates the efficacy and futility boundaries at each look. It allows modifying the design and tracking the design update history.
License: MIT + file LICENSE
Depends: methods
Suggests: roxygen2
NeedsCompilation: no
Packaged: 2024-05-17 23:14:42 UTC; hz029
Repository: CRAN
Date/Publication: 2024-05-17 23:50:08 UTC

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Package inldata updated to version 1.2.1 with previous version 1.1.5 dated 2024-04-15

Title: Collection of Datasets for the USGS-INL Monitoring Networks
Description: A collection of analysis-ready datasets for the U.S. Geological Survey - Idaho National Laboratory (USGS-INL) groundwater and surface-water monitoring networks, administered by the USGS-INL Project Office in cooperation with the U.S. Department of Energy. The data collected from wells and surface-water stations at the Idaho National Laboratory and surrounding areas have been used to describe the effects of waste disposal on water contained in the eastern Snake River Plain aquifer, located in the southeastern part of Idaho, and the availability of water for long-term consumptive and industrial use. The package includes long-term monitoring records dating back to measurements from 1922. Geospatial data describing the areas from which samples were collected or observations were made are also included in the package. Bundling this data into a single package significantly reduces the magnitude of data processing for researchers and provides a way to distribute the data along with its docume [...truncated...]
Author: Jason C. Fisher [aut, cre] , Allison R. Trcka [aut] , Kerri C. Treinen [aut]
Maintainer: Jason C. Fisher <jfisher@usgs.gov>

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Package evinf updated to version 0.8.10 with previous version 0.8.9 dated 2024-05-16

Title: Inference with Extreme Value Inflated Count Data
Description: Allows users to model and draw inferences from extreme value inflated count data, and to evaluate these models and compare to non extreme-value inflated counterparts. The package is built to be compatible with standard presentation tools such as 'broom', 'tidy', and 'modelsummary'.
Author: David Randahl [cre, aut], Johan Vegelius [aut]
Maintainer: David Randahl <david.randahl@pcr.uu.se>

Diff between evinf versions 0.8.9 dated 2024-05-16 and 0.8.10 dated 2024-05-17

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Package ggseqplot updated to version 0.8.4 with previous version 0.8.3 dated 2023-09-22

Title: Render Sequence Plots using 'ggplot2'
Description: A set of wrapper functions that mainly re-produces most of the sequence plots rendered with TraMineR::seqplot(). Whereas 'TraMineR' uses base R to produce the plots this library draws on 'ggplot2'. The plots are produced on the basis of a sequence object defined with TraMineR::seqdef(). The package automates the reshaping and plotting of sequence data. Resulting plots are of class 'ggplot', i.e. components can be added and tweaked using '+' and regular 'ggplot2' functions.
Author: Marcel Raab [aut, cre]
Maintainer: Marcel Raab <marcel.raab@gmail.com>

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Package iGraphMatch updated to version 2.0.5 with previous version 2.0.4 dated 2024-02-13

Title: Tools for Graph Matching
Description: Versatile tools and data for graph matching analysis with various forms of prior information that supports working with 'igraph' objects, matrix objects, or lists of either.
Author: Daniel Sussman [aut, cre], Zihuan Qiao [aut], Joshua Agterberg [ctb], Lujia Wang [ctb], Vince Lyzinski [ctb]
Maintainer: Daniel Sussman <sussman@bu.edu>

Diff between iGraphMatch versions 2.0.4 dated 2024-02-13 and 2.0.5 dated 2024-05-17

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Package nbpMatching updated to version 1.5.5 with previous version 1.5.4 dated 2023-08-18

Title: Functions for Optimal Non-Bipartite Matching
Description: Perform non-bipartite matching and matched randomization. A "bipartite" matching utilizes two separate groups, e.g. smokers being matched to nonsmokers or cases being matched to controls. A "non-bipartite" matching creates mates from one big group, e.g. 100 hospitals being randomized for a two-arm cluster randomized trial or 5000 children who have been exposed to various levels of secondhand smoke and are being paired to form a greater exposure vs. lesser exposure comparison. At the core of a non-bipartite matching is a N x N distance matrix for N potential mates. The distance between two units expresses a measure of similarity or quality as mates (the lower the better). The 'gendistance()' and 'distancematrix()' functions assist in creating this. The 'nonbimatch()' function creates the matching that minimizes the total sum of distances between mates; hence, it is referred to as an "optimal" matching. The 'assign.grp()' function aids in performing a matched randomization. Note bipartit [...truncated...]
Author: Cole Beck [aut, cre], Bo Lu [aut], Robert Greevy [aut]
Maintainer: Cole Beck <cole.beck@vumc.org>

Diff between nbpMatching versions 1.5.4 dated 2023-08-18 and 1.5.5 dated 2024-05-17

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Package ecce updated to version 3.0.1 with previous version 2.0.6 dated 2023-10-09

Title: Translate English Sentence into Chinese, or Translate Chinese Sentence into English
Description: If translate English or Chinese sentence, there is a faster way for R user. You can pass in an English or Chinese sentence, ecce package support both English and Chinese translation. It also support browse translation results in website. In addition, also support obtain the pinyin of the Chinese character, you can more easily understand the pronunciation of the Chinese character.
Author: Xinyuan Chu [aut, cre]
Maintainer: Xinyuan Chu <chuxinyuan@outlook.com>

Diff between ecce versions 2.0.6 dated 2023-10-09 and 3.0.1 dated 2024-05-17

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Package apache.sedona updated to version 1.6.0 with previous version 1.5.3 dated 2024-05-10

Title: R Interface for Apache Sedona
Description: R interface for 'Apache Sedona' based on 'sparklyr' (<https://sedona.apache.org>).
Author: Apache Sedona [aut, cre], Jia Yu [ctb, cph], Yitao Li [aut, cph] , The Apache Software Foundation [cph], RStudio [cph]
Maintainer: Apache Sedona <private@sedona.apache.org>

Diff between apache.sedona versions 1.5.3 dated 2024-05-10 and 1.6.0 dated 2024-05-17

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Package usmapdata updated to version 0.3.0 with previous version 0.2.2 dated 2024-03-08

Title: Mapping Data for 'usmap' Package
Description: Provides a container for data used by the 'usmap' package. The data used by 'usmap' has been extracted into this package so that the file size of the 'usmap' package can be reduced greatly. The data in this package will be updated roughly once per year as new map data files are provided by the US Census Bureau.
Author: Paolo Di Lorenzo [aut, cre]
Maintainer: Paolo Di Lorenzo <dilorenzo@hey.com>

Diff between usmapdata versions 0.2.2 dated 2024-03-08 and 0.3.0 dated 2024-05-17

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New package streamConnect with initial version 0.0-1
Package: streamConnect
Version: 0.0-1
Date: 2024-05-16
Encoding: UTF-8
Title: Connecting Stream Mining Components Using Sockets and Web Services
Description: Adds functionality to connect stream mining components from package stream using sockets and Web services. The package can be used create distributed workflows and create plumber-based Web services which can be deployed on most common cloud services.
Depends: stream (>= 2.0-0)
Imports: plumber, callr, httr, readr, stringr, jsonlite
Suggests: knitr, httpuv, rmarkdown
BugReports: https://github.com/mhahsler/streamConnect
License: GPL-3
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2024-05-17 15:55:01 UTC; hahsler
Author: Michael Hahsler [aut, cre, cph]
Maintainer: Michael Hahsler <mhahsler@lyle.smu.edu>
Repository: CRAN
Date/Publication: 2024-05-17 16:20:03 UTC

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New package mgwrhw with initial version 1.1.1.5
Package: mgwrhw
Title: Displays GWR (Geographically Weighted Regression) and Mixed GWR Output and Map
Version: 1.1.1.5
Description: Display processing results using the GWR (Geographically Weighted Regression) method, display maps, and show the results of the Mixed GWR (Mixed Geographically Weighted Regression) model which automatically selects global variables based on variability between regions. This function refers to Yasin, & Purhadi. (2012). "Mixed Geographically Weighted Regression Model (Case Study the Percentage of Poor Households in Mojokerto 2008)". European Journal of Scientific Research, 188-196. <https://www.researchgate.net/profile/Hasbi-Yasin-2/publication/289689583_Mixed_geographically_weighted_regression_model_case_study_The_percentage_of_poor_households_in_Mojokerto_2008/links/58e46aa40f7e9bbe9c94d641/Mixed-geographically-weighted-regression-model-case-study-The-percentage-of-poor-households-in-Mojokerto-2008.pdf>.
License: GPL-3
Encoding: UTF-8
LazyData: true
LazyDataCompression: xz
Author: Asy-Syaja'ul Haqqul Amin [cre, aut], Waris Marsisno [aut]
Maintainer: Asy-Syaja'ul Haqqul Amin <haqqul.amin06@gmail.com>
Imports: spgwr, sf, psych, ggplot2, dplyr, tidyr
Suggests: knitr, rmarkdown, testthat (>= 3.0.0)
VignetteBuilder: knitr
Depends: R (>= 2.10)
NeedsCompilation: no
Packaged: 2024-05-17 16:08:05 UTC; User
Repository: CRAN
Date/Publication: 2024-05-17 16:30:02 UTC

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Package marginalizedRisk updated to version 2024.5-17 with previous version 2024.1-27 dated 2024-01-27

Title: Estimating Marginalized Risk
Description: Estimates risk as a function of a marker by integrating over other covariates in a conditional risk model.
Author: Youyi Fong [cre], Peter Gilbert [aut], Marco Carone [aut]
Maintainer: Youyi Fong <youyifong@gmail.com>

Diff between marginalizedRisk versions 2024.1-27 dated 2024-01-27 and 2024.5-17 dated 2024-05-17

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Package cmahalanobis updated to version 0.2.0 with previous version 0.1.0 dated 2024-02-20

Title: Calculate the Mahalanobis Distance for a Given List of Data Frames with Factors
Description: It provides a function that calculates the Mahalanobis distance between each pair of species in a list of data frames. Each data frame contains the observations of a species with some factors. Mahalanobis distance is a measure of dissimilarity between two vectors of multivariate random variables, based on the covariance matrix. This distance is useful for statistical matching or fusion of data, that is the integration of two data sources that refer to the same target population and that share some variables.
Author: Flavio Gioia
Maintainer: Flavio Gioia <flaviogioia.fg@gmail.com>

Diff between cmahalanobis versions 0.1.0 dated 2024-02-20 and 0.2.0 dated 2024-05-17

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Package clinDataReview updated to version 1.5.2 with previous version 1.5.1 dated 2024-04-24

Title: Clinical Data Review Tool
Description: Creation of interactive tables, listings and figures ('TLFs') and associated report for exploratory analysis of data in a clinical trial, e.g. for clinical oversight activities. Interactive figures include sunburst, treemap, scatterplot, line plot and barplot of counts data. Interactive tables include table of summary statistics (as counts of adverse events, enrollment table) and listings. Possibility to compare data (summary table or listing) across two data batches/sets. A clinical data review report is created via study-specific configuration files and template 'R Markdown' reports contained in the package.
Author: Laure Cougnaud [aut, cre], Michela Pasetto [aut], Lennart Tuijnder [aut], Adriaan Blommaert [aut], Arne De Roeck [ctb, rev] , Open Analytics [cph]
Maintainer: Laure Cougnaud <laure.cougnaud@openanalytics.eu>

Diff between clinDataReview versions 1.5.1 dated 2024-04-24 and 1.5.2 dated 2024-05-17

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New package spbal with initial version 1.0.0
Package: spbal
Title: Spatially Balanced Sampling Algorithms
Version: 1.0.0
Description: Encapsulates a number of spatially balanced sampling algorithms, namely, Balanced Acceptance Sampling (equal, unequal, seed point, panels), Halton frames (for discretizing a continuous resource), Halton Iterative Partitioning (equal probability) and Simple Random Sampling. Robertson, B. L., Brown, J. A., McDonald, T. and Jaksons, P. (2013) <doi:10.1111/biom.12059>. Robertson, B. L., McDonald, T., Price, C. J. and Brown, J. A. (2017) <doi:10.1016/j.spl.2017.05.004>. Robertson, B. L., McDonald, T., Price, C. J. and Brown, J. A. (2018) <doi:10.1007/s10651-018-0406-6>. Robertson, B. L., van Dam-Bates, P. and Gansell, O. (2021a) <doi:10.1007/s10651-020-00481-1>.
Depends: R (>= 3.6.0)
License: MIT + file LICENSE
Encoding: UTF-8
Imports: units, sf, Rcpp
SystemRequirements: C++17
Suggests: knitr, rmarkdown, testthat (>= 3.0.0), bookdown, ggplot2, gridExtra
VignetteBuilder: knitr
LinkingTo: Rcpp, RcppThread
NeedsCompilation: yes
Packaged: 2024-05-17 11:27:33 UTC; phil
Author: Phil Davies [aut, cre], Blair Robertson [aut], Paul van Dam-Bates [aut], Oliver Gansell [aut]
Maintainer: Phil Davies <philip.davies@canterbury.ac.nz>
Repository: CRAN
Date/Publication: 2024-05-17 16:00:02 UTC

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Package good updated to version 1.0.2 with previous version 1.0.1 dated 2021-05-10

Title: Good Regression
Description: Fit Good regression models to count data (Tur et al., 2021) <doi:10.48550/arXiv.2105.01557>. The package provides functions for model estimation and model prediction. Density, distribution function, quantile function and random generation for the Good distribution are also provided.
Author: Jordi Tur [aut, cre], David Morina [ctb], Pere Puig [ctb], Argimiro Arratia [ctb], Alejandra Cabana [ctb], David Agis [ctb], Amanda Fernandez-Fontelo [aut]
Maintainer: Jordi Tur <jjtur@crm.cat>

Diff between good versions 1.0.1 dated 2021-05-10 and 1.0.2 dated 2024-05-17

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Package stan4bart updated to version 0.0-8 with previous version 0.0-7 dated 2023-12-08

Title: Bayesian Additive Regression Trees with Stan-Sampled Parametric Extensions
Description: Fits semiparametric linear and multilevel models with non-parametric additive Bayesian additive regression tree (BART; Chipman, George, and McCulloch (2010) <doi:10.1214/09-AOAS285>) components and Stan (Stan Development Team (2021) <https://mc-stan.org/>) sampled parametric ones. Multilevel models can be expressed using 'lme4' syntax (Bates, Maechler, Bolker, and Walker (2015) <doi:10.18637/jss.v067.i01>).
Author: Vincent Dorie [aut, cre] , Ben Goodrich [ctb] , Jonah Gabry [ctb] , Imad Ali [ctb] , Sam Brilleman [ctb] , Paul-Christian Burkner [ctb] , Joshua Pritikin [ctb] , Andrew Gelman [ctb] , Bob Carpenter [ctb] , Matt Hoffman [ctb] , Daniel Lee [ctb] , Mich [...truncated...]
Maintainer: Vincent Dorie <vdorie@gmail.com>

Diff between stan4bart versions 0.0-7 dated 2023-12-08 and 0.0-8 dated 2024-05-17

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Package rqlm updated to version 1.3-1 with previous version 1.2-1 dated 2024-01-19

Title: Modified Poisson and Least-Squares Regressions for Binary Outcome
Description: Modified Poisson and least-squares regression analyses for binary outcomes of Zou (2004) <doi:10.1093/aje/kwh090> and Cheung (2007) <doi:10.1093/aje/kwm223> have been standard multivariate analysis methods to estimate risk ratio and risk difference in clinical and epidemiological studies. This R package involves an easy-to-handle function to implement these analyses by simple commands. Also, recent studies have shown the ordinary robust variance estimator possibly has serious bias under small or moderate sample size situations for these methods. This package also provides computational tools to calculate alternative accurate confidence intervals (Noma and Gosho (2024) <Forthcoming>).
Author: Hisashi Noma [aut, cre]
Maintainer: Hisashi Noma <noma@ism.ac.jp>

Diff between rqlm versions 1.2-1 dated 2024-01-19 and 1.3-1 dated 2024-05-17

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Package Rnanoflann updated to version 0.0.3 with previous version 0.0.2 dated 2023-12-05

Title: Extremely Fast Nearest Neighbor Search
Description: Finds the k nearest neighbours for every point in a given dataset using Jose Luis' 'nanoflann' library. There is support for exact searches, fixed radius searches with 'kd' trees and two distances, the 'Euclidean' and 'Manhattan'. For more information see <https://github.com/jlblancoc/nanoflann>. Also, the 'nanoflann' library is exported and ready to be used via the linking to mechanism.
Author: Manos Papadakis [aut, cre, cph], Jose Luis Blanco [aut, cph], Michail Tsagris [ctb]
Maintainer: Manos Papadakis <papadakm95@gmail.com>

Diff between Rnanoflann versions 0.0.2 dated 2023-12-05 and 0.0.3 dated 2024-05-17

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Package clusterMI updated to version 1.1.0 with previous version 1.0.0 dated 2024-03-12

Title: Cluster Analysis with Missing Values by Multiple Imputation
Description: Allows clustering of incomplete observations by addressing missing values using multiple imputation. For achieving this goal, the methodology consists in three steps, following Audigier and Niang 2022 <doi:10.1007/s11634-022-00519-1>. I) Missing data imputation using dedicated models. Four multiple imputation methods are proposed, two are based on joint modelling and two are fully sequential methods, as discussed in Audigier et al. (2021) <doi:10.48550/arXiv.2106.04424>. II) cluster analysis of imputed data sets. Six clustering methods are available (distances-based or model-based), but custom methods can also be easily used. III) Partition pooling. The set of partitions is aggregated using Non-negative Matrix Factorization based method. An associated instability measure is computed by bootstrap (see Fang, Y. and Wang, J., 2012 <doi:10.1016/j.csda.2011.09.003>). Among applications, this instability measure can be used to choose a number of clusters with missing value [...truncated...]
Author: Vincent Audigier [aut, cre] , Hang Joon Kim [ctb]
Maintainer: Vincent Audigier <vincent.audigier@cnam.fr>

Diff between clusterMI versions 1.0.0 dated 2024-03-12 and 1.1.0 dated 2024-05-17

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Package clinUtils updated to version 0.2.0 with previous version 0.1.5 dated 2024-04-23

Title: General Utility Functions for Analysis of Clinical Data
Description: Utility functions to facilitate the import, the reporting and analysis of clinical data. Example datasets in 'SDTM' and 'ADaM' format, containing a subset of patients/domains from the 'CDISC Pilot 01 study' are also available as R datasets to demonstrate the package functionalities.
Author: Laure Cougnaud [aut, cre], Michela Pasetto [aut], Arne De Roeck [rev] , Open Analytics [cph]
Maintainer: Laure Cougnaud <laure.cougnaud@openanalytics.eu>

Diff between clinUtils versions 0.1.5 dated 2024-04-23 and 0.2.0 dated 2024-05-17

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Package ggiraph updated to version 0.8.10 with previous version 0.8.9 dated 2024-02-24

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 0.8.9 dated 2024-02-24 and 0.8.10 dated 2024-05-17

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 ggiraph-0.8.10/ggiraph/NAMESPACE                                                          |    1 
 ggiraph-0.8.10/ggiraph/NEWS.md                                                            |   17 ++
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Package bipartite updated to version 2.20 with previous version 2.19 dated 2023-11-30

Title: Visualising Bipartite Networks and Calculating Some (Ecological) Indices
Description: Functions to visualise webs and calculate a series of indices commonly used to describe pattern in (ecological) webs. It focuses on webs consisting of only two levels (bipartite), e.g. pollination webs or predator-prey-webs. Visualisation is important to get an idea of what we are actually looking at, while the indices summarise different aspects of the web's topology.
Author: Carsten F. Dormann [aut, cre] , Jochen Fruend [aut] , Bernd Gruber [aut] , Stephen Beckett [ctb] , Mariano Devoto [ctb] , Gabriel M.F. Felix [ctb] , Jose M. Iriondo [ctb] , Tore Opsahl [ctb] , Rafael B.P. Pinheiro [ctb] , Rouven Strauss [ctb], Diego [...truncated...]
Maintainer: Carsten F. Dormann <carsten.dormann@biom.uni-freiburg.de>

Diff between bipartite versions 2.19 dated 2023-11-30 and 2.20 dated 2024-05-17

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Package rmarkdown updated to version 2.27 with previous version 2.26 dated 2024-03-05

Title: Dynamic Documents for R
Description: Convert R Markdown documents into a variety of formats.
Author: JJ Allaire [aut], Yihui Xie [aut, cre] , Christophe Dervieux [aut] , Jonathan McPherson [aut], Javier Luraschi [aut], Kevin Ushey [aut], Aron Atkins [aut], Hadley Wickham [aut], Joe Cheng [aut], Winston Chang [aut], Richard Iannone [aut] , Andrew Dun [...truncated...]
Maintainer: Yihui Xie <xie@yihui.name>

Diff between rmarkdown versions 2.26 dated 2024-03-05 and 2.27 dated 2024-05-17

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Package NMA updated to version 1.4-3 with previous version 1.4-2 dated 2024-02-18

Title: Network Meta-Analysis Based on Multivariate Meta-Analysis Models
Description: Network meta-analysis tools based on contrast-based approach using the multivariate meta-analysis and meta-regression models (Noma et al. (2023) <Forthcoming>). Standard analysis tools for network meta-analysis and meta-regression (e.g., synthesis analysis, ranking analysis, and creating league table) are available by simple commands. For inconsistency analyses, the local and global inconsistency tests based on the Higgins' design-by-treatment interaction model can be applied. Also, the side-splitting and the Jackson's random inconsistency model are available. Standard graphical tools for network meta-analysis (e.g., network plot, ranked forest plot, and transitivity analysis) can also be utilized. For the synthesis analyses, the Noma-Hamura's improved REML (restricted maximum likelihood)-based methods (Noma et al. (2023) <doi:10.1002/jrsm.1652> <doi:10.1002/jrsm.1651>) are adopted as the default methods.
Author: Hisashi Noma [aut, cre] , Kazushi Maruo [aut], Shiro Tanaka [aut], Toshi A. Furukawa [aut]
Maintainer: Hisashi Noma <noma@ism.ac.jp>

Diff between NMA versions 1.4-2 dated 2024-02-18 and 1.4-3 dated 2024-05-17

 DESCRIPTION  |    8 ++++----
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 5 files changed, 41 insertions(+), 27 deletions(-)

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New package crosstalkr with initial version 1.0.5
Package: crosstalkr
Title: Analysis of Graph-Structured Data with a Focus on Protein-Protein Interaction Networks
Version: 1.0.5
Description: Provides a general toolkit for drug target identification. We include functionality to reduce large graphs to subgraphs and prioritize nodes. In addition to being optimized for use with generic graphs, we also provides support to analyze protein-protein interactions networks from online repositories. For more details on core method, refer to Weaver et al. (2021) <https://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1008755>.
License: GPL (>= 3)
Imports: rlang, magrittr, withr, readr, dplyr, stringr, tidyr, tibble, igraph (>= 1.2.0), Matrix, ensembldb, foreach, doParallel, Rcpp, iterators, ggplot2, STRINGdb
LinkingTo: Rcpp
Encoding: UTF-8
Suggests: tidygraph, ggraph, testthat (>= 2.0.0), knitr, EnsDb.Hsapiens.v86, rmarkdown, here
VignetteBuilder: knitr
Depends: R (>= 2.10)
NeedsCompilation: yes
Packaged: 2024-05-03 14:08:32 UTC; dtw43
Author: Davis Weaver [aut, cre]
Maintainer: Davis Weaver <davis.weaver@case.edu>
Repository: CRAN
Date/Publication: 2024-05-17 11:40:09 UTC

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New package crosslag with initial version 0.1.0
Package: crosslag
Title: Perform Linear or Nonlinear Cross Lag Analysis
Version: 0.1.0
Maintainer: Yaxin Li <LYX010308@163.com>
Description: Linear or nonlinear cross-lagged panel model can be built from input data. Users can choose the appropriate method from three methods for constructing nonlinear cross lagged models. These three methods include polynomial regression, generalized additive model and generalized linear mixed model.In addition, a function for determining linear relationships is provided. Relevant knowledge of cross lagged models can be learned through the paper by Fredrik Falkenström (2024) <doi:10.1016/j.cpr.2024.102435> and the paper by A Gasparrini (2010) <doi:10.1002/sim.3940>.
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
Depends: R (>= 4.3.0)
Imports: gamm4 (>= 0.2.6), ggplot2 (>= 3.5.0), lavaan (>= 0.6.17), mgcv (>= 1.9.1), rms (>= 6.8.0), ggpubr (>= 0.6.0), stats (>= 4.3.2), utils (>= 3.1.0)
NeedsCompilation: no
Packaged: 2024-05-16 01:37:56 UTC; lyx01
Author: Yaxin Li [aut, cre]
Repository: CRAN
Date/Publication: 2024-05-17 10:10:03 UTC

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New package smlePH with initial version 0.1.0
Package: smlePH
Title: Sieve Maximum Full Likelihood Estimation for the Right-Censored Proportional Hazards Model
Version: 0.1.0
Author: Susan Halabi [aut], Taehwa Choi [aut, cre], Yuan Wu [aut]
Maintainer: Taehwa Choi <tchoi@sungshin.ac.kr>
Description: Fitting the full likelihood proportional hazards model and extracting the residuals.
URL: https://github.com/taehwa015/smlePH/
BugReports: https://github.com/taehwa015/smlePH/issues/
License: GPL (>= 3)
Encoding: UTF-8
Suggests: knitr, rmarkdown
Imports: MASS, splines2, stats
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2024-05-16 23:26:48 UTC; taehwa
Repository: CRAN
Date/Publication: 2024-05-17 09:40:02 UTC

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Package rhosa updated to version 0.3.0 with previous version 0.2.0 dated 2022-01-21

Title: Higher-Order Spectral Analysis
Description: Higher-order spectra or polyspectra of time series, such as bispectrum and bicoherence, have been investigated in abundant literature and applied to problems of signal detection in a wide range of fields. This package aims to provide a simple API to estimate and analyze them. The current implementation is based on Brillinger and Irizarry (1998) <doi:10.1016/S0165-1684(97)00217-X> for estimating bispectrum or bicoherence, Lii and Helland (1981) <doi:10.1145/355958.355961> for cross-bispectrum, and Kim and Powers (1979) <doi:10.1109/TPS.1979.4317207> for cross-bicoherence.
Author: Takeshi Abe [aut, cre]
Maintainer: Takeshi Abe <tabe@fixedpoint.jp>

Diff between rhosa versions 0.2.0 dated 2022-01-21 and 0.3.0 dated 2024-05-17

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New package MajMinKmeans with initial version 0.1.0
Package: MajMinKmeans
Title: k-Means Algorithm with a Majorization-Minimization Method
Version: 0.1.0
Maintainer: Sheikhi Ayyub <sheikhy.a@uk.ac.ir>
Description: A hybrid of the K-means algorithm and a Majorization-Minimization method to introduce a robust clustering. The reference paper is: Julien Mairal, (2015) <doi:10.1137/140957639>. The two most important functions in package 'MajMinKmeans' are cluster_km() and cluster_MajKm(). Cluster_km() clusters data without Majorization-Minimization and cluster_MajKm() clusters data with Majorization-Minimization method. Both of these functions calculate the sum of squares (SS) of clustering. Another useful function is MajMinOptim(), which helps to find the optimum values of the Majorization-Minimization estimator.
Imports: MASS
License: GPL-3
Encoding: UTF-8
NeedsCompilation: no
Packaged: 2024-05-16 04:24:18 UTC; macbook
Author: Sheikhi Ayyub [aut, cre], Yaghoobi Mohammad Ali [aut]
Repository: CRAN
Date/Publication: 2024-05-17 09:20:09 UTC

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New package lme4breeding with initial version 1.0.1
Package: lme4breeding
Version: 1.0.1
Date: 2024-05-01
Title: Relationship-Based Mixed-Effects Models
Maintainer: Giovanny Covarrubias-Pazaran <cova_ruber@live.com.mx>
Description: Fit relationship-based and customized mixed-effects models with complex variance-covariance structures using the 'lme4' machinery. The core computational algorithms are implemented using the 'Eigen' 'C++' library for numerical linear algebra and 'RcppEigen' 'glue'.
Depends: R(>= 3.0.0), lme4 (>= 1.0), Matrix (>= 1.0), methods, crayon
LazyLoad: yes
LazyData: yes
License: GPL (>= 2)
NeedsCompilation: yes
Author: Giovanny Covarrubias-Pazaran [aut, cre]
Repository: CRAN
Suggests: rmarkdown, knitr, orthopolynom, RSpectra
VignetteBuilder: knitr
Packaged: 2024-05-16 13:20:35 UTC; giovannycovarrubias
Date/Publication: 2024-05-17 09:20:03 UTC

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New package KMEANS.KNN with initial version 0.1.0
Package: KMEANS.KNN
Title: KMeans and KNN Clustering Package
Version: 0.1.0
Description: Implementation of Kmeans clustering algorithm and a supervised KNN (K Nearest Neighbors) learning method. It allows users to perform unsupervised clustering and supervised classification on their datasets. Additional features include data normalization, imputation of missing values, and the choice of distance metric. The package also provides functions to determine the optimal number of clusters for Kmeans and the best k-value for KNN: knn_Function(), find_Knn_best_k(), KMEANS_FUNCTION(), and find_Kmeans_best_k().
License: GPL-3
Encoding: UTF-8
Imports: factoextra, cluster, ggplot2, stats, assertthat, class, caret, grDevices
Suggests: knitr, rmarkdown, testthat (>= 3.0.0)
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2024-05-16 14:54:49 UTC; USER
Author: LALLOGO Lassane [aut, cre]
Maintainer: LALLOGO Lassane <lassanelallogo2002@gmail.com>
Repository: CRAN
Date/Publication: 2024-05-17 09:20:12 UTC

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New package CleaningValidation with initial version 1.0
Package: CleaningValidation
Version: 1.0
Title: Cleaning Validation Functions for Pharmaceutical Cleaning Process
Description: Provides essential Cleaning Validation functions for complying with pharmaceutical cleaning process regulatory standards. The package includes non-parametric methods to analyze drug active-ingredient residue (DAR), cleaning agent residue (CAR), and microbial colonies (Mic) for non-Poisson distributions. Additionally, Poisson methods are provided for Mic analysis when Mic data follow a Poisson distribution.
License: GPL-3
Depends: R (>= 4.3.0)
Imports: dplyr (>= 1.0.0), rlang, ggplot2 (>= 3.3.3), cowplot (>= 1.1.1), dunn.test, boot, AER, lme4
Encoding: UTF-8
Author: Mohamed Chan [aut], Wendy Lou [aut], Xiande Yang [aut, cre]
Maintainer: Xiande Yang <xyang1@apotex.com>
URL: https://github.com/ChandlerXiandeYang/CleaningValidation
NeedsCompilation: no
Packaged: 2024-05-16 01:35:03 UTC; 14373
Repository: CRAN
Date/Publication: 2024-05-17 09:10:21 UTC

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Package broom updated to version 1.0.6 with previous version 1.0.5 dated 2023-06-09

Title: Convert Statistical Objects into Tidy Tibbles
Description: Summarizes key information about statistical objects in tidy tibbles. This makes it easy to report results, create plots and consistently work with large numbers of models at once. Broom provides three verbs that each provide different types of information about a model. tidy() summarizes information about model components such as coefficients of a regression. glance() reports information about an entire model, such as goodness of fit measures like AIC and BIC. augment() adds information about individual observations to a dataset, such as fitted values or influence measures.
Author: David Robinson [aut], Alex Hayes [aut] , Simon Couch [aut, cre] , Posit Software, PBC [cph, fnd], Indrajeet Patil [ctb] , Derek Chiu [ctb], Matthieu Gomez [ctb], Boris Demeshev [ctb], Dieter Menne [ctb], Benjamin Nutter [ctb], Luke Johnston [ctb], Be [...truncated...]
Maintainer: Simon Couch <simon.couch@posit.co>

Diff between broom versions 1.0.5 dated 2023-06-09 and 1.0.6 dated 2024-05-17

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New package bootsurv with initial version 0.0.1
Package: bootsurv
Title: Bootstrap Methods for Complete Survey Data
Version: 0.0.1
Depends: R (>= 3.5.0)
Description: Bootstrap resampling methods have been widely studied in the context of survey data. This package implements various bootstrap resampling techniques tailored for survey data, with a focus on stratified simple random sampling and stratified two-stage cluster sampling. It provides tools for precise and consistent bootstrap variance estimation for population totals, means, and quartiles. Additionally, it enables easy generation of bootstrap samples for in-depth analysis.
License: GPL-3
Imports: MASS, stats
Encoding: UTF-8
LazyData: true
NeedsCompilation: no
Packaged: 2024-05-16 16:28:50 UTC; zeinabmashreghi
Author: Zeinab Mashreghi [aut, cre]
Maintainer: Zeinab Mashreghi <z.mashreghi@uwinnipeg.ca>
Repository: CRAN
Date/Publication: 2024-05-17 09:40:05 UTC

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New package bbnet with initial version 1.0
Package: bbnet
Title: Create Simple Predictive Models on Bayesian Belief Networks
Version: 1.0
Maintainer: Victoria Dominguez Almela <vda1r22@soton.ac.uk>
Description: A system to build, visualise and evaluate Bayesian belief networks. The methods are described in Stafford et al. (2015) <doi:10.12688/f1000research.5981.1>.
License: GPL (>= 2)
URL: https://github.com/vda1r22/bbnet
BugReports: https://github.com/vda1r22/bbnet/issues
Depends: R (>= 3.5.0), dplyr, ggplot2, grid, igraph, tibble
Encoding: UTF-8
LazyData: true
Suggests: knitr, rmarkdown, testthat
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2024-05-16 16:26:01 UTC; vda1r22
Author: Rick Stafford [cph, aut] , Victoria Dominguez Almela [cre, aut]
Repository: CRAN
Date/Publication: 2024-05-17 09:40:08 UTC

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Package goeveg updated to version 0.7.5 with previous version 0.7.4 dated 2024-02-26

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, merging of taxa 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 KernSmooth updated to version 2.23-24 with previous version 2.23-22 dated 2023-07-10

Title: Functions for Kernel Smoothing Supporting Wand & Jones (1995)
Description: Functions for kernel smoothing (and density estimation) corresponding to the book: Wand, M.P. and Jones, M.C. (1995) "Kernel Smoothing".
Author: Matt Wand [aut], Cleve Moler [ctb] , Brian Ripley [trl, cre, ctb]
Maintainer: Brian Ripley <ripley@stats.ox.ac.uk>

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Package fflr (with last version 2.3.0) was removed from CRAN

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

2024-05-03 2.3.0
2024-03-28 2.2.4
2024-03-11 2.2.3
2024-02-03 2.2.2
2024-01-12 2.2.1
2023-09-14 2.2.0
2022-09-12 2.1.0
2022-04-06 2.0.3
2022-01-17 2.0.2
2021-11-17 2.0.1
2021-11-08 2.0.0
2021-10-05 1.9.2

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Package HypergeoMat (with last version 4.0.2) was removed from CRAN

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

2023-01-30 4.0.2

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Package RAZIAD (with last version 0.0.1) was removed from CRAN

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

2024-05-02 0.0.1

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Package QTLEMM updated to version 1.5.4 with previous version 1.5.3 dated 2024-04-26

Title: QTL Mapping and Hotspots Detection
Description: For QTL mapping, this package comprises several functions designed to execute diverse tasks, such as simulating or analyzing data, calculating significance thresholds, and visualizing QTL mapping results. The single-QTL or multiple-QTL method, which enables the fitting and comparison of various statistical models, is employed to analyze the data for estimating QTL parameters. The models encompass linear regression, permutation tests, normal mixture models, and truncated normal mixture models. The Gaussian stochastic process is utilized to compute significance thresholds for QTL detection on a genetic linkage map within experimental populations. Two types of data, complete genotyping, and selective genotyping data from various experimental populations, including backcross, F2, recombinant inbred (RI) populations, and advanced intercrossed (AI) populations, are considered in the QTL mapping analysis. For QTL hotspot detection, statistical methods can be developed based on either utilizin [...truncated...]
Author: Ping-Yuan Chung [cre], Chen-Hung Kao [aut], Y.-T. Guo [aut], H.-N. Ho [aut], H.-I. Lee [aut], P.-Y. Wu [aut], M.-H. Yang [aut], M.-H. Zeng [aut]
Maintainer: Ping-Yuan Chung <pychung@webmail.stat.sinica.edu.tw>

Diff between QTLEMM versions 1.5.3 dated 2024-04-26 and 1.5.4 dated 2024-05-17

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Package melt updated to version 1.11.4 with previous version 1.11.3 dated 2024-04-12

Title: Multiple Empirical Likelihood Tests
Description: Performs multiple empirical likelihood tests. It offers an easy-to-use interface and flexibility in specifying hypotheses and calibration methods, extending the framework to simultaneous inferences. The core computational routines are implemented using the 'Eigen' 'C++' library and 'RcppEigen' interface, with 'OpenMP' for parallel computation. Details of the testing procedures are provided in Kim, MacEachern, and Peruggia (2023) <doi:10.1080/10485252.2023.2206919>. A companion paper by Kim, MacEachern, and Peruggia (2024) <doi:10.18637/jss.v108.i05> is available for further information. This work was supported by the U.S. National Science Foundation under Grants No. SES-1921523 and DMS-2015552.
Author: Eunseop Kim [aut, cph, cre], Steven MacEachern [ctb, ths], Mario Peruggia [ctb, ths], Pierre Chausse [rev], Alex Stringer [rev]
Maintainer: Eunseop Kim <markean@pm.me>

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Package gatoRs updated to version 1.0.2 with previous version 1.0.1 dated 2023-11-30

Title: Geographic and Taxonomic Occurrence R-Based Scrubbing
Description: Streamlines downloading and cleaning biodiversity data from Integrated Digitized Biocollections (iDigBio) and the Global Biodiversity Information Facility (GBIF).
Author: Natalie N. Patten [aut, cre] , Michelle L. Gaynor [aut] , Douglas E. Soltis [ctb] , Pamela S. Soltis [ctb]
Maintainer: Natalie N. Patten <natalienpatten@gmail.com>

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