Wed, 13 Oct 2021

New package vegtable with initial version 0.1.7
Package: vegtable
Version: 0.1.7
Encoding: UTF-8
Title: Handling Vegetation Data Sets
Depends: R (>= 3.5.0), taxlist
Imports: foreign, methods, knitr, qdapRegex, sp, stringi, vegdata
Suggests: rmarkdown, roxygen2, testthat, vegan
Description: Import and handling data from vegetation-plot databases, especially data stored in 'Turboveg 2' (<https://www.synbiosys.alterra.nl/turboveg/>). Also import/export routines for exchange of data with 'Juice' (<https://www.sci.muni.cz/botany/juice/>) are implemented.
LazyData: true
License: GPL (>= 2)
URL: https://github.com/kamapu/vegtable
BugReports: https://github.com/kamapu/vegtable/issues
NeedsCompilation: no
Packaged: 2021-10-13 15:23:38 UTC; miguel
Author: Miguel Alvarez [aut, cre] (<https://orcid.org/0000-0003-1500-1834>)
Maintainer: Miguel Alvarez <kamapu78@gmail.com>
Repository: CRAN
Date/Publication: 2021-10-13 21:10:02 UTC

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New package effectFusion with initial version 1.1.3
Package: effectFusion
Version: 1.1.3
Date: 2021-10-13
Title: Bayesian Effect Fusion for Categorical Predictors
Depends: R (>= 3.3), mcclust
Imports: Matrix, MASS, bayesm, cluster, GreedyEPL, gridExtra, ggplot2, methods, utils, stats
Description: Variable selection and Bayesian effect fusion for categorical predictors in linear and logistic regression models. Effect fusion aims at the question which categories have a similar effect on the response and therefore can be fused to obtain a sparser representation of the model. Effect fusion and variable selection can be obtained either with a prior that has an interpretation as spike and slab prior on the level effect differences or with a sparse finite mixture prior on the level effects. The regression coefficients are estimated with a flat uninformative prior after model selection or by taking model averages. Posterior inference is accomplished by an MCMC sampling scheme which makes use of a data augmentation strategy (Polson, Scott & Windle (2013) <doi:10.1080/01621459.2013.829001>) based on latent Polya-Gamma random variables in the case of logistic regression. The code for data augmentation is taken from Polson et al. (2013) <doi:10.1080/01621459.2013.829001>, who own the copyright.
License: GPL-3
Encoding: UTF-8
LazyData: true
NeedsCompilation: yes
Repository: CRAN
Packaged: 2021-10-13 19:20:51 UTC; User
Author: Daniela Pauger [aut], Magdalena Leitner [aut, cre], Helga Wagner [aut] (<https://orcid.org/0000-0002-7003-9512>), Gertraud Malsiner-Walli [aut] (<https://orcid.org/0000-0002-1213-4749>), Nicholas G. Polson [ctb], James G. Scott [ctb], Jesse Windle [ctb], Bettina Grün [ctb] (<https://orcid.org/0000-0001-7265-4773>)
Maintainer: Magdalena Leitner <effectfusion.jku@gmail.com>
Date/Publication: 2021-10-13 21:10:05 UTC

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Package EESPCA updated to version 0.5.0 with previous version 0.4.0 dated 2021-10-06

Title: Eigenvectors from Eigenvalues Sparse Principal Component Analysis (EESPCA)
Description: Contains logic for computing sparse principal components via the EESPCA method, which is based on an approximation of the eigenvector/eigenvalue identity. Includes logic to support execution of the TPower and rifle sparse PCA methods, as well as logic to estimate the sparsity parameters used by EESPCA, TPower and rifle via cross-validation to minimize the out-of-sample reconstruction error. H. Robert Frost (2021) <arXiv:2006.01924>.
Author: H. Robert Frost
Maintainer: H. Robert Frost <rob.frost@dartmouth.edu>

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Package viridis updated to version 0.6.2 with previous version 0.6.1 dated 2021-05-11

Title: Colorblind-Friendly Color Maps for R
Description: Color maps designed to improve graph readability for readers with common forms of color blindness and/or color vision deficiency. The color maps are also perceptually-uniform, both in regular form and also when converted to black-and-white for printing. This package also contains 'ggplot2' bindings for discrete and continuous color and fill scales. A lean version of the package called 'viridisLite' that does not include the 'ggplot2' bindings can be found at <https://cran.r-project.org/package=viridisLite>.
Author: Simon Garnier [aut, cre], Noam Ross [ctb, cph], Bob Rudis [ctb, cph], Marco Sciaini [ctb, cph], Antônio Pedro Camargo [ctb, cph], Cédric Scherer [ctb, cph]
Maintainer: Simon Garnier <garnier@njit.edu>

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Package tpn updated to version 1.1 with previous version 1.0 dated 2021-07-19

Title: Truncated Positive Normal Model and Extensions
Description: Provide data generation and estimation tools for the truncated positive normal model discussed in Gomez, Olmos, Varela and Bolfarine (2018) <doi:10.1007/s11766-018-3354-x>, the slash truncated positive normal distribution and the bimodal truncated positive normal distribution.
Author: Diego Gallardo [aut, cre], Hector J. Gomez [aut], Yolanda M. Gomez [aut]
Maintainer: Diego Gallardo <diego.gallardo@uda.cl>

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Package survSNP updated to version 0.25 with previous version 0.24 dated 2016-06-29

Title: Power Calculations for SNP Studies with Censored Outcomes
Description: Conduct asymptotic and empirical power and sample size calculations for Single-Nucleotide Polymorphism (SNP) association studies with right censored time to event outcomes.
Author: Kouros Owzar, Zhiguo Li, Nancy Cox, Sin-Ho Jung and Chanhee Yi
Maintainer: Alexander Sibley <dcibioinformatics@duke.edu>

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Package smacpod updated to version 2.3 with previous version 2.2.2 dated 2021-09-14

Title: Statistical Methods for the Analysis of Case-Control Point Data
Description: Statistical methods for analyzing case-control point data. Methods include the ratio of kernel densities, the difference in K Functions, the spatial scan statistic, and q nearest neighbors of cases.
Author: Joshua French [aut, cre] (<https://orcid.org/0000-0002-9708-3353>)
Maintainer: Joshua French <joshua.french@ucdenver.edu>

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Package RoBMA updated to version 2.1.0 with previous version 2.0.0 dated 2021-07-08

Title: Robust Bayesian Meta-Analyses
Description: A framework for estimating ensembles of meta-analytic models (assuming either presence or absence of the effect, heterogeneity, and publication bias). The RoBMA framework uses Bayesian model-averaging to combine the competing meta-analytic models into a model ensemble, weights the posterior parameter distributions based on posterior model probabilities and uses Bayes factors to test for the presence or absence of the individual components (e.g., effect vs. no effect; Bartoš et al., 2021, <doi:10.31234/osf.io/kvsp7>; Maier, Bartoš & Wagenmakers, in press, <doi:10.31234/osf.io/u4cns>). Users can define a wide range of non-informative or informative prior distributions for the effect size, heterogeneity, and publication bias components (including selection models and PET-PEESE). The package provides convenient functions for summary, visualizations, and fit diagnostics.
Author: František Bartoš [aut, cre] (<https://orcid.org/0000-0002-0018-5573>), Maximilian Maier [aut] (<https://orcid.org/0000-0002-9873-6096>), Eric-Jan Wagenmakers [ths] (<https://orcid.org/0000-0003-1596-1034>), Joris Goosen [ctb], Matthew Denwood [cph] (Original copyright holder of some modified code where indicated.), Martyn Plummer [cph] (Original copyright holder of some modified code where indicated.)
Maintainer: František Bartoš <f.bartos96@gmail.com>

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Package preregr updated to version 0.1.9 with previous version 0.1.3 dated 2021-09-30

Title: Specify (Pre)Registrations and Export Them Human- And Machine-Readably
Description: Preregistrations, or more generally, registrations, enable explicit timestamped and (often but not necessarily publicly) frozen documentation of plans and expectations as well as decisions and justifications. In research, preregistrations are commonly used to clearly document plans and facilitate justifications of deviations from those plans, as well as decreasing the effects of publication bias by enabling identification of research that was conducted but not published. Like reporting guidelines, (pre)registration forms often have specific structures that facilitate systematic reporting of important items. The 'preregr' package facilitates specifying (pre)registrations in R and exporting them to a human-readable format (using R Markdown partials or exporting to an 'HTML' file) as well as human-readable embedded data (using 'JSON'), as well as importing such exported (pre)registration specifications from such embedded 'JSON'.
Author: Gjalt-Jorn Peters [aut, cre] (<https://orcid.org/0000-0002-0336-9589>)
Maintainer: Gjalt-Jorn Peters <gjalt-jorn@behaviorchange.eu>

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Package pkgload updated to version 1.2.3 with previous version 1.2.2 dated 2021-09-11

Title: Simulate Package Installation and Attach
Description: Simulates the process of installing a package and then attaching it. This is a key part of the 'devtools' package as it allows you to rapidly iterate while developing a package.
Author: Hadley Wickham [aut], Jim Hester [aut, cre], Winston Chang [aut], RStudio [cph], R Core team [ctb] (Some namespace and vignette code extracted from base R)
Maintainer: Jim Hester <jim.hester@rstudio.com>

Diff between pkgload versions 1.2.2 dated 2021-09-11 and 1.2.3 dated 2021-10-13

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More information about pkgload at CRAN
Permanent link

Package optimx updated to version 2021-10.12 with previous version 2021-6.12 dated 2021-06-13

Title: Expanded Replacement and Extension of the 'optim' Function
Description: Provides a replacement and extension of the optim() function to call to several function minimization codes in R in a single statement. These methods handle smooth, possibly box constrained functions of several or many parameters. Note that function 'optimr()' was prepared to simplify the incorporation of minimization codes going forward. Also implements some utility codes and some extra solvers, including safeguarded Newton methods. Many methods previously separate are now included here. This is the version for CRAN.
Author: John C Nash [aut, cre], Ravi Varadhan [aut], Gabor Grothendieck [ctb]
Maintainer: John C Nash <nashjc@uottawa.ca>

Diff between optimx versions 2021-6.12 dated 2021-06-13 and 2021-10.12 dated 2021-10-13

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Package occCite updated to version 0.5.0 with previous version 0.4.9 dated 2021-07-23

Title: Querying and Managing Large Biodiversity Occurrence Datasets
Description: Facilitates the gathering of biodiversity occurrence data from disparate sources. Metadata is managed throughout the process to facilitate reporting and enhanced ability to repeat analyses.
Author: Hannah L. Owens [aut, cre] (<https://orcid.org/0000-0003-0071-1745>), Cory Merow [aut] (<https://orcid.org/0000-0003-0561-053X>), Brian Maitner [aut] (<https://orcid.org/0000-0002-2118-9880>), Jamie M. Kass [aut] (<https://orcid.org/0000-0002-9432-895X>), Vijay Barve [aut] (<https://orcid.org/0000-0002-4852-2567>), Robert P. Guralnick [aut] (<https://orcid.org/0000-0001-6682-1504>)
Maintainer: Hannah L. Owens <hannah.owens@gmail.com>

Diff between occCite versions 0.4.9 dated 2021-07-23 and 0.5.0 dated 2021-10-13

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Package IFC updated to version 0.1.2 with previous version 0.1.1 dated 2020-12-18

Title: Tools for Imaging Flow Cytometry
Description: Contains several tools to treat imaging flow cytometry data from 'ImageStream®' and 'FlowSight®' cytometers ('Amnis®', part of 'Luminex®'). Provides an easy and simple way to read and write .fcs, .rif, .cif and .daf files. Information such as masks, features, regions and populations set within these files can be retrieved for each single cell. In addition, raw data such as images stored can also be accessed. Users, may hopefully increase their productivity thanks to dedicated functions to extract, visualize, manipulate and export 'IFC' data. Toy data example can be installed through the 'IFCdata' package of approximately 32 MB, which is available in a 'drat' repository <https://gitdemont.github.io/IFCdata/>. See file 'COPYRIGHTS' and file 'AUTHORS' for a list of copyright holders and authors.
Author: Yohann Demont [aut, cre], Gautier Stoll [ctb], Guido Kroemer [ldr], Jean-Pierre Marolleau [ldr], Loïc Garçon [ldr]
Maintainer: Yohann Demont <git.demont@gmail.com>

Diff between IFC versions 0.1.1 dated 2020-12-18 and 0.1.2 dated 2021-10-13

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More information about IFC at CRAN
Permanent link

Package GNRS updated to version 0.3.4 with previous version 0.3.3 dated 2021-10-08

Title: Access the 'Geographic Name Resolution Service'
Description: Provides tools for interacting with the 'geographic name resolution service' ('GNRS') API <https://github.com/ojalaquellueva/gnrs> and associated functionality. The 'GNRS' is a batch application for resolving & standardizing political division names against standard name in the geonames database <http://www.geonames.org/>. The 'GNRS' resolves political division names at three levels: country, state/province and county/parish. Resolution is performed in a series of steps, beginning with direct matching to standard names, followed by direct matching to alternate names in different languages, followed by direct matching to standard codes (such as ISO and FIPS codes). If direct matching fails, the 'GNRS' attempts to match to standard and then alternate names using fuzzy matching, but does not perform fuzzing matching of political division codes. The 'GNRS' works down the political division hierarchy, stopping at the current level if all matches fail. In other words, if a country cannot be matched, the 'GNRS' does not attempt to match state or county.
Author: Brad Boyle [aut], Brian Maitner [aut, cre]
Maintainer: Brian Maitner <bmaitner@gmail.com>

Diff between GNRS versions 0.3.3 dated 2021-10-08 and 0.3.4 dated 2021-10-13

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 vignettes/GNRS.Rmd                         |    2 
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More information about GNRS at CRAN
Permanent link

Package geosphere updated to version 1.5-14 with previous version 1.5-10 dated 2019-05-26

Title: Spherical Trigonometry
Description: Spherical trigonometry for geographic applications. That is, compute distances and related measures for angular (longitude/latitude) locations.
Author: Robert J. Hijmans [cre, aut], Charles Karney [ctb] (GeographicLib), Ed Williams [ctb], Chris Vennes [ctb]
Maintainer: Robert J. Hijmans <r.hijmans@gmail.com>

Diff between geosphere versions 1.5-10 dated 2019-05-26 and 1.5-14 dated 2021-10-13

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Package CLONETv2 updated to version 2.2.1 with previous version 2.1.0 dated 2019-05-20

Title: Clonality Estimates in Tumor
Description: Analyze data from next-generation sequencing experiments on genomic samples. 'CLONETv2' offers a set of functions to compute allele specific copy number and clonality from segmented data and SNPs position pileup. The package has also calculated the clonality of single nucleotide variants given read counts at mutated positions. The package has been developed at the laboratory of Computational and Functional Oncology, Department of CIBIO, University of Trento (Italy), under the supervision of prof Francesca Demichelis. References: Prandi et al. (2014) <doi:10.1186/s13059-014-0439-6>; Carreira et al. (2014) <doi:10.1126/scitranslmed.3009448>; Romanel et al. (2015) <doi:10.1126/scitranslmed.aac9511>.
Author: Davide Prandi [aut], Alessandro Romanel [ctb], Tarcisio Fedrizzi [ctb], Yari Ciani [cre]
Maintainer: Yari Ciani <yari.ciani@unitn.it>

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Package archive updated to version 1.1.1 with previous version 1.1.0 dated 2021-08-04

Title: Multi-Format Archive and Compression Support
Description: Bindings to 'libarchive' <http://www.libarchive.org> the Multi-format archive and compression library. Offers R connections and direct extraction for many archive formats including 'tar', 'ZIP', '7-zip', 'RAR', 'CAB' and compression formats including 'gzip', 'bzip2', 'compress', 'lzma' and 'xz'.
Author: Jim Hester [aut, cre] (<https://orcid.org/0000-0002-2739-7082>), Ondrej Holy [cph] (archive_write_add_filter implementation), RStudio [cph, fnd]
Maintainer: Jim Hester <jim.hester@rstudio.com>

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Package raveio updated to version 0.0.5 with previous version 0.0.4 dated 2021-08-05

Title: File-System Toolbox for RAVE Project
Description: Includes multiple cross-platform read/write interfaces for 'RAVE' project. 'RAVE' stands for "R analysis and visualization of human intracranial electroencephalography data". The whole project aims at providing powerful free-source package that analyze brain recordings from patients with electrodes placed on the cortical surface or inserted into the brain. 'raveio' as part of this project provides tools to read/write neurophysiology data from/to 'RAVE' file structure, as well as several popular formats including 'EDF(+)', 'Matlab', 'BIDS-iEEG', and 'HDF5', etc. Documentation and examples about 'RAVE' project are provided at <https://openwetware.org/wiki/RAVE>, and the paper by John F. Magnotti, Zhengjia Wang, Michael S. Beauchamp (2020) <doi:10.1016/j.neuroimage.2020.117341>; see 'citation("raveio")' for details.
Author: Zhengjia Wang [aut, cre], Beauchamp lab [cph, fnd]
Maintainer: Zhengjia Wang <dipterix.wang@gmail.com>

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Package tcplfit2 updated to version 0.1.3 with previous version 0.1.2 dated 2021-10-01

Title: Concentration-Response Modeling of HTS or Transcriptomics Data
Description: Performs the basic concentration response curve fitting used in the 'tcpl' package. It is a substitute for the original tcplFit() function (and sub-functions) and allows a wider variety of concentration-response models. All of the models included in the 'BMDExpress' package are now part of this package, and the output includes a calculation of the bmd (Benchmark Dose or concentration) value.
Author: Thomas Sheffield [aut], Richard Judson [ctb], Jason Brown [ctb, cre], Sarah E. Davidson [ctb]
Maintainer: Jason Brown <brown.jason@epa.gov>

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Package PMCMRplus updated to version 1.9.2 with previous version 1.9.0 dated 2021-01-15

Title: Calculate Pairwise Multiple Comparisons of Mean Rank Sums Extended
Description: For one-way layout experiments the one-way ANOVA can be performed as an omnibus test. All-pairs multiple comparisons tests (Tukey-Kramer test, Scheffe test, LSD-test) and many-to-one tests (Dunnett test) for normally distributed residuals and equal within variance are available. Furthermore, all-pairs tests (Games-Howell test, Tamhane's T2 test, Dunnett T3 test, Ury-Wiggins-Hochberg test) and many-to-one (Tamhane-Dunnett Test) for normally distributed residuals and heterogeneous variances are provided. Van der Waerden's normal scores test for omnibus, all-pairs and many-to-one tests is provided for non-normally distributed residuals and homogeneous variances. The Kruskal-Wallis, BWS and Anderson-Darling omnibus test and all-pairs tests (Nemenyi test, Dunn test, Conover test, Dwass-Steele-Critchlow- Fligner test) as well as many-to-one (Nemenyi test, Dunn test, U-test) are given for the analysis of variance by ranks. Non-parametric trend tests (Jonckheere test, Cuzick test, Johnson-Mehrotra test, Spearman test) are included. In addition, a Friedman-test for one-way ANOVA with repeated measures on ranks (CRBD) and Skillings-Mack test for unbalanced CRBD is provided with consequent all-pairs tests (Nemenyi test, Siegel test, Miller test, Conover test, Exact test) and many-to-one tests (Nemenyi test, Demsar test, Exact test). A trend can be tested with Pages's test. Durbin's test for a two-way balanced incomplete block design (BIBD) is given in this package as well as Gore's test for CRBD with multiple observations per cell is given. Outlier tests, Mandel's k- and h statistic as well as functions for Type I error and Power analysis as well as generic summary, print and plot methods are provided.
Author: Thorsten Pohlert [aut, cre] (<https://orcid.org/0000-0003-3855-3025>)
Maintainer: Thorsten Pohlert <thorsten.pohlert@gmx.de>

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Package peacesciencer updated to version 0.6.0 with previous version 0.5.0 dated 2021-06-21

Title: Various Tools and Data for Quantitative Peace Science
Description: These are useful tools and data sets for the study of quantitative peace science. The goal for this package is to include tools and data sets for doing original research that mimics well what a user would have to previously get from a software package that may not be well-sourced or well-supported. Those software bundles were useful the extent to which they encourage replications of long-standing analyses by starting the data-generating process from scratch. However, a lot of the functionality can be done relatively quickly and more transparently in the R programming language.
Author: Steve Miller [aut, cre] (<https://orcid.org/0000-0003-4072-6263>)
Maintainer: Steve Miller <steven.v.miller@gmail.com>

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Package SWMPrExtension updated to version 2.1.0 with previous version 2.0.0 dated 2021-10-01

Title: Functions for Analyzing and Plotting Estuary Monitoring Data
Description: Tools for performing routine analysis and plotting tasks with environmental data from the System Wide Monitoring Program of the National Estuarine Research Reserve System <http://cdmo.baruch.sc.edu/>. This package builds on the functionality of the SWMPr package <https://cran.r-project.org/package=SWMPr>, which is used to retrieve and organize the data. The combined set of tools address common challenges associated with continuous time series data for environmental decision making, and are intended for use in annual reporting activities. References: Beck, Marcus W. (2016) <ISSN 2073-4859><https://journal.r-project.org/archive/2016-1/beck.pdf> Rudis, Bob (2014) <https://rud.is/b/2014/11/16/moving-the-earth-well-alaska-hawaii-with-r/>. United States Environmental Protection Agency (2015) <https://cfpub.epa.gov/si/si_public_record_Report.cfm?Lab=OWOW&dirEntryId=327030>. United States Environmental Protection Agency (2012) <http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.646.1973&rep=rep1&type=pdf>.
Author: Julie Padilla [aut, ctb], Marcus Beck [ctb], Kimberly Cressman [ctb], Dave Eslinger [cre, ctb], Bob Rudis [ctb]
Maintainer: Dave Eslinger <dave.eslinger@noaa.gov>

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Package geomorph updated to version 4.0.1 with previous version 4.0.0 dated 2021-04-02

Title: Geometric Morphometric Analyses of 2D/3D Landmark Data
Description: Read, manipulate, and digitize landmark data, generate shape variables via Procrustes analysis for points, curves and surfaces, perform shape analyses, and provide graphical depictions of shapes and patterns of shape variation.
Author: Dean Adams [aut, cre], Michael Collyer [aut], Antigoni Kaliontzopoulou [aut], Erica Baken [aut]
Maintainer: Dean Adams <dcadams@iastate.edu>

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Package dipsaus updated to version 0.1.9 with previous version 0.1.8 dated 2021-09-06

Title: A Dipping Sauce for Data Analysis and Visualizations
Description: Works as an "add-on" to packages like 'shiny', 'future', as well as 'rlang', and provides utility functions. Just like dipping sauce adding flavors to potato chips or pita bread, 'dipsaus' for data analysis and visualizations adds handy functions and enhancements to popular packages. The goal is to provide simple solutions that are frequently asked for online, such as how to synchronize 'shiny' inputs without freezing the app, or how to get memory size on 'Linux' or 'MacOS' system. The enhancements roughly fall into these four categories: 1. 'shiny' input widgets; 2. high-performance computing using 'RcppParallel' and 'future' package; 3. modify R calls and convert among numbers, strings, and other objects. 4. utility functions to get system information such like CPU chip-set, memory limit, etc.
Author: Zhengjia Wang [aut, cre]
Maintainer: Zhengjia Wang <dipterix.wang@gmail.com>

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Package threeBrain updated to version 0.2.3 with previous version 0.2.1 dated 2021-08-03

Title: 3D Brain Visualization
Description: A fast, interactive cross-platform, and easy to share 'WebGL'-based 3D brain viewer that visualizes 'FreeSurfer' and/or 'AFNI/SUMA' surfaces. The viewer widget can be either standalone or embedded into 'R-shiny' applications. The standalone version only require a web browser with 'WebGL2' support (for example, 'Chrome'). It can be inserted into any websites; see <https://dipterix.org/project/threebrain/>). as an example. The 'R-shiny' support allows the 3D viewer to be dynamically generated from reactive user inputs. This feature has been fully adopted by 'RAVE' <https://openwetware.org/wiki/RAVE>, an interactive toolbox to analyze 'iEEG/eCoG' data. Documentation about 'threeBrain' is provided by <https://dipterix.org/threeBrain/> and several vignettes included in this package. To cite the package, please check our 'NeuroImage' paper by Magnotti, Wang, and Beauchamp (2020, <doi:10.1016/j.neuroimage.2020.117341>), or see 'citation("threeBrain")' for details.
Author: Zhengjia Wang [aut, cre, cph], John Magnotti [aut], Xiang Zhang [ctb, res], Brian Metzger [res], Elizabeth Nesbitt [res], Meng Li [ths], Michael Beauchamp [aut, dtc]
Maintainer: Zhengjia Wang <dipterix.wang@gmail.com>

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Package OpenSpecy updated to version 0.9.3 with previous version 0.9.2 dated 2021-05-20

Title: Analyze, Process, Identify, and Share, Raman and (FT)IR Spectra
Description: Raman and (FT)IR spectral analysis tool for plastic particles and other environmental samples (Cowger et al. 2021, <doi:10.1021/acs.analchem.1c00123>). Supported features include reading spectral data files (.asp, .csv, .jdx, .spc, .spa, .0), Savitzky-Golay smoothing of spectral intensities with smooth_intens(), correcting background noise with subtr_bg() in accordance with Zhao et al. (2007) <doi:10.1366/000370207782597003>, and identifying spectra using an onboard reference library (Cowger et al. 2020, <doi:10.1177/0003702820929064>). Analyzed spectra can be shared with the Open Specy community. A Shiny app is available via run_app() or online at <https://wincowger.shinyapps.io/OpenSpecy/>.
Author: Win Cowger [cre, aut] (<https://orcid.org/0000-0001-9226-3104>), Zacharias Steinmetz [aut] (<https://orcid.org/0000-0001-6675-5033>), Andrew Gray [ctb] (<https://orcid.org/0000-0003-2252-7367>), Hannah Hapich [ctb] (<https://orcid.org/0000-0003-0000-6632>), Jennifer Lynch [ctb, dtc] (<https://orcid.org/0000-0003-3572-8782>), Hannah De Frond [ctb, dtc] (<https://orcid.org/0000-0003-1199-0727>), Keenan Munno [ctb, dtc] (<https://orcid.org/0000-0003-2916-5944>), Chelsea Rochman [ctb, dtc] (<https://orcid.org/0000-0002-7624-711X>), Sebastian Primpke [ctb, dtc] (<https://orcid.org/0000-0001-7633-8524>), Orestis Herodotou [ctb, dtc]
Maintainer: Win Cowger <wincowger@gmail.com>

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Package EMVS updated to version 1.2.1 with previous version 1.1 dated 2019-12-13

Title: The Expectation-Maximization Approach to Bayesian Variable Selection
Description: An efficient expectation-maximization algorithm for fitting Bayesian spike-and-slab regularization paths for linear regression. Rockova and George (2014) <doi:10.1080/01621459.2013.869223>.
Author: Veronika Rockova [aut,cre], Gemma Moran [aut]
Maintainer: Gemma Moran <gm2918@columbia.edu>

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Package distill updated to version 1.3 with previous version 1.2 dated 2021-01-13

Title: 'R Markdown' Format for Scientific and Technical Writing
Description: Scientific and technical article format for the web. 'Distill' articles feature attractive, reader-friendly typography, flexible layout options for visualizations, and full support for footnotes and citations.
Author: JJ Allaire [aut, cre] (<https://orcid.org/0000-0003-0174-9868>), Rich Iannone [aut], Alison Presmanes Hill [aut] (<https://orcid.org/0000-0002-8082-1890>), Yihui Xie [aut] (<https://orcid.org/0000-0003-0645-5666>), RStudio, Inc. [cph], Google LLC [ctb, cph] (https://distill.pub/guide/), Nick Williams [ctb, cph] (https://wicky.nillia.ms/headroom.js/), Denis Demchenko [ctb, cph] (https://github.com/lancedikson/bowser), The Polymer Authors [ctb, cph] (https://www.webcomponents.org/polyfills/), Gábor Csárdi [ctb, cph] (whoami), JooYoung Seo [ctb] (<https://orcid.org/0000-0002-4064-6012>)
Maintainer: JJ Allaire <jj@rstudio.com>

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Package regressoR updated to version 2.0.1 with previous version 2.0.0 dated 2021-09-23

Title: Regression Data Analysis System
Description: Perform a supervised data analysis on a database through a 'shiny' graphical interface. It includes methods such as linear regression, penalized regression, k-nearest neighbors, decision trees, ada boosting, extreme gradient boosting, random forest, neural networks, deep learning and support vector machines.
Author: Oldemar Rodriguez R. [aut, cre], Andres Navarro D. [ctb, prg], Diego Jimenez A. [ctb, prg], Ariel Arroyo S. [ctb, prg]
Maintainer: Oldemar Rodriguez R. <oldemar.rodriguez@ucr.ac.cr>

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Package qrcode updated to version 0.1.4 with previous version 0.1.3 dated 2021-07-02

Title: Generate QRcodes with R
Description: Create QRcode in R.
Author: Victor Teh [aut] (Original author), Thierry Onkelinx [aut, cre] (Author of the reimplemented functions, <https://orcid.org/0000-0001-8804-4216>)
Maintainer: Thierry Onkelinx <thierry.onkelinx@inbo.be>

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Package robis updated to version 2.8.2 with previous version 2.8.1 dated 2021-09-30

Title: Ocean Biodiversity Information System (OBIS) Client
Description: Client for the Ocean Biodiversity Information System (<https://obis.org>).
Author: Pieter Provoost [cre, aut], Samuel Bosch [aut], Ward Appeltans [ctb], OBIS [cph]
Maintainer: Pieter Provoost <pieterprovoost@gmail.com>

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Package microsamplingDesign updated to version 1.0.8 with previous version 1.0.7 dated 2020-04-05

Title: Finding Optimal Microsampling Designs for Non-Compartmental Pharmacokinetic Analysis
Description: Find optimal microsampling designs for non-compartmental pharacokinetic analysis using a general simulation methodology: Algorithm III of Barnett, Helen, Helena Geys, Tom Jacobs, and Thomas Jaki. (2017) "Optimal Designs for Non-Compartmental Analysis of Pharmacokinetic Studies. (currently unpublished)" This methodology consist of (1) specifying a pharmacokinetic model including variability among animals; (2) generating possible sampling times; (3) evaluating performance of each time point choice on simulated data; (4) generating possible schemes given a time point choice and additional constraints and finally (5) evaluating scheme performance on simulated data. The default settings differ from the article of Barnett and others, in the default pharmacokinetic model used and the parameterization of variability among animals. Details can be found in the package vignette. A 'shiny' web application is included, which guides users from model parametrization to optimal microsampling scheme.
Author: Adriaan Blommaert [aut, cre], Daan Seynaeve [ctb], Helen Barnett [ctb], Helena Geys [ctb], Tom Jacobs [ctb], Fetene Tekle [ctb], Thomas Jaki [ctb]
Maintainer: Adriaan Blommaert <adriaan.blommaert@openanalytics.eu>

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Package likelihoodR updated to version 1.0.5 with previous version 1.0.4 dated 2021-05-03

Title: Likelihood Analyses for Common Statistical Tests
Description: A collection of functions that calculate the log likelihood (support) for a range of statistical tests. Where possible the likelihood function and likelihood interval for the observed data are displayed. The evidential approach used here is based on the book "Likelihood" by A.W.F. Edwards (1992, ISBN-13 : 978-0801844430), "Statistical Evidence" by R. Royall (1997, ISBN-13 : 978-0412044113), S.N. Goodman & R. Royall (2011) <doi:10.2105/AJPH.78.12.1568>, "Understanding Psychology as a Science" by Z. Dienes (2008, ISBN-13 : 978-0230542310), S. Glover & P. Dixon <https://link.springer.com/article/10.3758/BF03196706> and others. This package accompanies "Evidence-Based Statistics" by P. Cahusac (2020, ISBN-13 : 978-1119549802).
Author: Peter Cahusac [aut, cre] (<https://orcid.org/0000-0003-4976-2834>)
Maintainer: Peter Cahusac <peteqsac@gmail.com>

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Package timereg updated to version 2.0.1 with previous version 2.0.0 dated 2021-05-20

Title: Flexible Regression Models for Survival Data
Description: Programs for Martinussen and Scheike (2006), `Dynamic Regression Models for Survival Data', Springer Verlag. Plus more recent developments. Additive survival model, semiparametric proportional odds model, fast cumulative residuals, excess risk models and more. Flexible competing risks regression including GOF-tests. Two-stage frailty modelling. PLS for the additive risk model. Lasso in the 'ahaz' package.
Author: Thomas Scheike with contributions from Torben Martinussen, Jeremy Silver and Klaus Holst
Maintainer: Thomas Scheike <ts@biostat.ku.dk>

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Package textshaping updated to version 0.3.6 with previous version 0.3.5 dated 2021-06-09

Title: Bindings to the 'HarfBuzz' and 'Fribidi' Libraries for Text Shaping
Description: Provides access to the text shaping functionality in the 'HarfBuzz' library and the bidirectional algorithm in the 'Fribidi' library. 'textshaping' is a low-level utility package mainly for graphic devices that expands upon the font tool-set provided by the 'systemfonts' package.
Author: Thomas Lin Pedersen [cre, aut] (<https://orcid.org/0000-0002-5147-4711>), RStudio [cph]
Maintainer: Thomas Lin Pedersen <thomas.pedersen@rstudio.com>

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Package systemfonts updated to version 1.0.3 with previous version 1.0.2 dated 2021-05-11

Title: System Native Font Finding
Description: Provides system native access to the font catalogue. As font handling varies between systems it is difficult to correctly locate installed fonts across different operating systems. The 'systemfonts' package provides bindings to the native libraries on Windows, macOS and Linux for finding font files that can then be used further by e.g. graphic devices. The main use is intended to be from compiled code but 'systemfonts' also provides access from R.
Author: Thomas Lin Pedersen [aut, cre] (<https://orcid.org/0000-0002-5147-4711>), Jeroen Ooms [aut] (<https://orcid.org/0000-0002-4035-0289>), Devon Govett [aut] (Author of font-manager), RStudio [cph]
Maintainer: Thomas Lin Pedersen <thomas.pedersen@rstudio.com>

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Package optiSolve updated to version 1.0 with previous version 0.1.2 dated 2020-03-10

Title: Linear, Quadratic, and Rational Optimization
Description: Solver for linear, quadratic, and rational programs with linear, quadratic, and rational constraints. A unified interface to different R packages is provided. Optimization problems are transformed into equivalent formulations and solved by the respective package. For example, quadratic programming problems with linear, quadratic and rational constraints can be solved by augmented Lagrangian minimization using package 'alabama', or by sequential quadratic programming using solver 'slsqp'. Alternatively, they can be reformulated as optimization problems with second order cone constraints and solved with package 'cccp'.
Author: Robin Wellmann
Maintainer: Robin Wellmann <r.wellmann@uni-hohenheim.de>

Diff between optiSolve versions 0.1.2 dated 2020-03-10 and 1.0 dated 2021-10-13

 DESCRIPTION        |   10 +++++-----
 MD5                |   22 +++++++++++-----------
 R/cop.R            |   17 +++++++++++------
 R/simplify.R       |    1 -
 R/solvecop.R       |    2 +-
 build/partial.rdb  |binary
 data/myQ.rda       |binary
 data/myQ1.rda      |binary
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Package rjags updated to version 4-12 with previous version 4-11 dated 2021-09-24

Title: Bayesian Graphical Models using MCMC
Description: Interface to the JAGS MCMC library.
Author: Martyn Plummer [aut, cre], Alexey Stukalov [ctb], Matt Denwood [ctb]
Maintainer: Martyn Plummer <martyn.plummer@gmail.com>

Diff between rjags versions 4-11 dated 2021-09-24 and 4-12 dated 2021-10-13

 DESCRIPTION     |    8 ++++----
 MD5             |    4 ++--
 R/windows/zzz.R |   20 ++++++++++++++------
 3 files changed, 20 insertions(+), 12 deletions(-)

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Package multiviewtest updated to version 2.0.1 with previous version 2.0.0 dated 2019-08-27

Title: Hypothesis Tests for Association Between Subgroups in Two Data Views
Description: Tests for association between subgroups in two multivariate data views, two network data views, or a multivariate data view and a network data view. (Reference 1: Gao, L.L., Bien, J., and Witten, D. (2020) "Are Clusterings of Multiple Data Views Independent?", <doi:10.1093/biostatistics/kxz001> and Reference 2: Gao, L.L., Witten, D., Bien, J. (2021) Testing for Association in Multi-View Network Data, <doi:10.1111/biom.13464>.)
Author: Lucy L. Gao [aut, cre]
Maintainer: Lucy L. Gao <lucy.gao@uwaterloo.ca>

Diff between multiviewtest versions 2.0.0 dated 2019-08-27 and 2.0.1 dated 2021-10-13

 DESCRIPTION                    |   15 +++++++--------
 MD5                            |   30 +++++++++++++++---------------
 NEWS.md                        |    7 +++----
 R/optimize_over_Pi.R           |    4 ++--
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 16 files changed, 110 insertions(+), 63 deletions(-)

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Package gslnls updated to version 1.0.2 with previous version 1.0.1 dated 2021-10-11

Title: GSL Nonlinear Least-Squares Fitting
Description: An R interface to nonlinear least-squares optimization with the GNU Scientific Library (GSL), see M. Galassi et al. (2009, ISBN:0954612078). The available trust region methods include the Levenberg-Marquadt algorithm with and without geodesic acceleration, and several variants of Powell's dogleg algorithm. Bindings are provided to tune a number of parameters affecting the low-level aspects of the trust region algorithms. The interface mimics R's nls() function and returns model objects inheriting from the same class.
Author: Joris Chau [aut, cre]
Maintainer: Joris Chau <joris.chau@openanalytics.eu>

Diff between gslnls versions 1.0.1 dated 2021-10-11 and 1.0.2 dated 2021-10-13

 DESCRIPTION       |    8 ++++----
 MD5               |    9 +++++----
 NEWS.md           |    4 ++++
 configure         |   18 +++++++++---------
 configure.ac      |    2 +-
 src/Makevars.ucrt |only
 6 files changed, 23 insertions(+), 18 deletions(-)

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Package gender updated to version 0.6.0 with previous version 0.5.4 dated 2020-05-15

Title: Predict Gender from Names Using Historical Data
Description: Infers state-recorded gender categories from first names and dates of birth using historical datasets. By using these datasets instead of lists of male and female names, this package is able to more accurately infer the gender of a name, and it is able to report the probability that a name was male or female. GUIDELINES: This method must be used cautiously and responsibly. Please be sure to see the guidelines and warnings about usage in the 'README' or the package documentation. See Blevins and Mullen (2015) <http://www.digitalhumanities.org/dhq/vol/9/3/000223/000223.html>.
Author: Lincoln Mullen [aut, cre] (<https://orcid.org/0000-0001-5103-6917>), Cameron Blevins [ctb], Ben Schmidt [ctb]
Maintainer: Lincoln Mullen <lincoln@lincolnmullen.com>

Diff between gender versions 0.5.4 dated 2020-05-15 and 0.6.0 dated 2021-10-13

 gender-0.5.4/gender/R/gender_df.R                   |only
 gender-0.5.4/gender/man/gender_df.Rd                |only
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 gender-0.6.0/gender/MD5                             |   33 -
 gender-0.6.0/gender/NAMESPACE                       |    1 
 gender-0.6.0/gender/NEWS.md                         |    5 
 gender-0.6.0/gender/R/gender-package.r              |    7 
 gender-0.6.0/gender/R/gender.R                      |    2 
 gender-0.6.0/gender/R/install-genderdata-package.R  |   12 
 gender-0.6.0/gender/README.md                       |   59 +--
 gender-0.6.0/gender/build/vignette.rds              |binary
 gender-0.6.0/gender/inst/CITATION                   |    2 
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 gender-0.6.0/gender/inst/doc/predicting-gender.html |  349 +++-----------------
 gender-0.6.0/gender/man/gender.Rd                   |    2 
 gender-0.6.0/gender/tests/testthat/test-ssa.r       |    2 
 gender-0.6.0/gender/vignettes/predicting-gender.Rmd |   39 --
 19 files changed, 137 insertions(+), 455 deletions(-)

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Package compareDF updated to version 2.3.2 with previous version 2.3.1 dated 2021-01-06

Title: Do a Git Style Diff of the Rows Between Two Dataframes with Similar Structure
Description: Compares two dataframes which have the same column structure to show the rows that have changed. Also gives a git style diff format to quickly see what has changed in addition to summary statistics.
Author: Alex Joseph [aut, cre]
Maintainer: Alex Joseph <alexsanjoseph@gmail.com>

Diff between compareDF versions 2.3.1 dated 2021-01-06 and 2.3.2 dated 2021-10-13

 DESCRIPTION                         |    8 ++--
 MD5                                 |    8 ++--
 NEWS.md                             |    4 ++
 R/fnsComparison.R                   |    7 +++-
 tests/testthat/test-fnsComparison.R |   60 +++++++++++++++++++++++++++++++++---
 5 files changed, 72 insertions(+), 15 deletions(-)

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Package ARTool updated to version 0.11.1 with previous version 0.11.0 dated 2021-02-24

Title: Aligned Rank Transform
Description: The aligned rank transform for nonparametric factorial ANOVAs as described by Wobbrock, Findlater, Gergle, and Higgins (2011) <doi:10.1145/1978942.1978963>. Also supports aligned rank transform contrasts as described by Elkin, Kay, Higgins, and Wobbrock (2021) <doi:10.1145/3472749.3474784>.
Author: Matthew Kay [aut, cre], Lisa A. Elkin [aut], James J. Higgins [aut], Jacob O. Wobbrock [aut]
Maintainer: Matthew Kay <mjskay@northwestern.edu>

Diff between ARTool versions 0.11.0 dated 2021-02-24 and 0.11.1 dated 2021-10-13

 DESCRIPTION                     |   23 +-
 MD5                             |   49 ++---
 NEWS.md                         |    8 
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 R/art.R                         |   14 -
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 R/art.con.internal.R            |    4 
 R/artlm.con.R                   |    6 
 R/data.R                        |   12 -
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 inst/doc/art-effect-size.html   |   17 +
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 tests/testthat/test.artlm.con.R |    8 
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 26 files changed, 340 insertions(+), 282 deletions(-)

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Package QTLEMM updated to version 1.1.0 with previous version 1.0.0 dated 2021-09-02

Title: QTL Mapping and Hotspots Detection
Description: For QTL mapping, it consists of several functions to perform various tasks, including simulating or analyzing data, computing the significance thresholds and visualizing the QTL mapping results. The single-QTL or multiple-QTL method that allows a host of statistical models to be fitted and compared is applied to analyze the data for the estimation of QTL parameters. The models include the linear regression, permutation test, normal mixture model and truncated normal mixture model. The Gaussian stochastic process is implemented to compute the significance thresholds for QTL detection onto a genetic linkage map in the experimental populations. Two types of data, the complete genotyping or selective genotyping data, from various experimental populations, including backcross, F2, recombinant inbred (RI) populations, advanced intercrossed (AI) populations, are considered in the QTL mapping analysis. For QTL hotpot detection, the statistical methods can be developed based on either using the individual-level data or using the summarized data. We have proposed a statistical framework that can handle both the individual-level data and summarized QTL data for QTL hotspots detection. Our statistical framework can overcome the underestimation of threshold arising from ignoring the correlation structure among traits, and also identify the different types of hotspots with very low computational cost during the detection process. Here, we attempt to provide the R codes of our QTL mapping and hotspot detection methods for general use in genes, genomics and genetics studies. The QTL mapping methods for the complete and selective genotyping designs are based on the multiple interval mapping (MIM) model proposed by Kao, C.-H. , Z.-B. Zeng and R. D. Teasdale (1999) <doi:10.1534/genetics.103.021642> and H.-I Lee, H.-A. Ho and C.-H. Kao (2014) <doi:10.1534/genetics.114.168385>, respectively. The QTL hotspot detection analysis is based on the method by Wu, P.-Y., M.-.H. Yang, and C.-H. Kao (2021) .
Author: Ping-Yuan Chung [cre], Chen-Hung Kao [aut]
Maintainer: Ping-Yuan Chung <pychung@webmail.stat.sinica.edu.tw>

Diff between QTLEMM versions 1.0.0 dated 2021-09-02 and 1.1.0 dated 2021-10-13

 DESCRIPTION                    |    6 +++---
 MD5                            |   38 +++++++++++++++++++-------------------
 R/EM.MIM.R                     |   12 ++++++++----
 R/EM.MIM2.R                    |   32 +++++++++++++++++++++++---------
 R/IM.search.R                  |   10 +++++-----
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 R/MIM.points.R                 |    2 +-
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 R/Q.make.R                     |    9 +++++++++
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 20 files changed, 93 insertions(+), 56 deletions(-)

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New package previsionio with initial version 11.3.0
Package: previsionio
Title: 'Prevision.io' R SDK
Version: 11.3.0
Description: For working with the 'Prevision.io' AI model management platform's API <https://prevision.io/>.
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: false
Imports: data.table, futile.logger, httr, jsonlite, Metrics, graphics, stats, utils, XML, magrittr, plotly
Suggests: testthat
Depends: R (>= 2.10)
NeedsCompilation: no
Packaged: 2021-10-13 08:37:12 UTC; Florian
Author: Florian Laroumagne [aut, cre], Prevision.io Inc [cph]
Maintainer: Florian Laroumagne <florian.laroumagne@prevision.io>
Repository: CRAN
Date/Publication: 2021-10-13 10:20:02 UTC

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New package lmForc with initial version 0.0.1
Package: lmForc
Title: Linear Model Forecasting
Version: 0.0.1
Description: Introduces in-sample, out-of-sample, pseudo out-of-sample, and benchmark linear model forecast tests and a new class for working with forecast data: Forecast.
License: GPL-3
Encoding: UTF-8
Depends: R (>= 3.6.0)
Imports: methods
Suggests: rmarkdown, knitr, testthat (>= 3.0.0)
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2021-10-12 22:35:13 UTC; nelsonrayl
Author: Nelson Rayl [aut, cre]
Maintainer: Nelson Rayl <nelsonrayl14@gmail.com>
Repository: CRAN
Date/Publication: 2021-10-13 10:10:02 UTC

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New package igcop with initial version 1.0.1
Package: igcop
Title: Computational Tools for the IG and IGL Copula Families
Version: 1.0.1
Description: Compute distributional quantities for an Integrated Gamma (IG) or Integrated Gamma Limit (IGL) copula, such as a cdf and density. Compute corresponding conditional quantities such as the cdf and quantiles. Generate data from an IG or IGL copula.
License: MIT + file LICENSE
Suggests: testthat, knitr, rmarkdown, tibble, covr, ggplot2
Encoding: UTF-8
VignetteBuilder: knitr
Imports: stats, vctrs, Rcpp, rlang
LinkingTo: Rcpp
NeedsCompilation: yes
Packaged: 2021-10-13 05:12:53 UTC; vincenzocoia
Author: Vincenzo Coia [aut, cre], Harry Joe [aut]
Maintainer: Vincenzo Coia <vincenzo.coia@gmail.com>
Repository: CRAN
Date/Publication: 2021-10-13 10:20:06 UTC

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

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

2021-01-10 0.1.1

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Package support.BWS updated to version 0.4-4 with previous version 0.4-3 dated 2021-01-28

Title: Tools for Case 1 Best-Worst Scaling
Description: Provides basic functions that support an implementation of object case (Case 1) best-worst scaling: a function for converting a two-level orthogonal main-effect design/balanced incomplete block design into questions; two functions for creating a data set suitable for analysis; a function for calculating count-based scores; a function for calculating shares of preference; and a function for generating artificial responses to questions. For details on best-worst scaling, see Louviere et al. (2015) <doi:10.1017/CBO9781107337855>.
Author: Hideo Aizaki
Maintainer: Hideo Aizaki <azk-r@spa.nifty.com>

Diff between support.BWS versions 0.4-3 dated 2021-01-28 and 0.4-4 dated 2021-10-13

 DESCRIPTION      |    8 ++++----
 MD5              |   12 ++++++------
 NAMESPACE        |    1 +
 NEWS             |    6 ++++++
 R/bws.count.R    |   30 +++++++++++++++++++++++++++---
 R/bws.dataset.R  |   29 ++++++++++++++++++++---------
 man/bws.count.Rd |    5 ++++-
 7 files changed, 68 insertions(+), 23 deletions(-)

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New package saotd with initial version 0.3.0
Package: saotd
Title: Sentiment Analysis of Twitter Data
Version: 0.3.0
Date: 2021-10-11
Maintainer: Evan Munson <evan.l.munson@gmail.com>
BugReports: https://github.com/evan-l-munson/saotd/issues
Description: This analytic is an in initial foray into sentiment analysis. This analytic will allow a user to access the Twitter API (once they create their own developer account), ingest tweets of their interest, clean / tidy data, perform topic modeling if interested, compute sentiment scores utilizing the Bing Lexicon, and output visualizations.
License: GPL (>= 2)
URL: https://github.com/evan-l-munson/saotd
Language: en-US
Imports: dplyr, widyr, stringr, tidytext, rtweet, tidyr, igraph, ggplot2, ggraph, scales, reshape2, lubridate, utils, stats, magrittr, ldatuning, topicmodels
Suggests: testthat (>= 3.0.0), knitr, rmarkdown, httr, base64enc, tibble, covr
Depends: R (>= 3.5.0)
VignetteBuilder: knitr
SystemRequirements: GSL (>=2.4), MPFR (>= 4.0.0), udunits2 (>=2.2.26-3)
Encoding: UTF-8
LazyLoad: true
NeedsCompilation: no
Packaged: 2021-10-12 14:00:34 UTC; munson
Author: Evan Munson [aut, cre] (<https://orcid.org/0000-0002-9958-6800>), Christopher Smith [aut] (<https://orcid.org/0000-0002-8288-270X>), Bradley Boehmke [aut] (<https://orcid.org/0000-0002-3611-8516>), Jason Freels [aut] (<https://orcid.org/0000-0002-2415-0340>)
Repository: CRAN
Date/Publication: 2021-10-13 09:50:02 UTC

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Package robustHD updated to version 0.7.1 with previous version 0.7.0 dated 2021-09-17

Title: Robust Methods for High-Dimensional Data
Description: Robust methods for high-dimensional data, in particular linear model selection techniques based on least angle regression and sparse regression.
Author: Andreas Alfons [aut, cre]
Maintainer: Andreas Alfons <alfons@ese.eur.nl>

Diff between robustHD versions 0.7.0 dated 2021-09-17 and 0.7.1 dated 2021-10-13

 robustHD-0.7.0/robustHD/inst/tests                |only
 robustHD-0.7.1/robustHD/DESCRIPTION               |   10 
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 robustHD-0.7.1/robustHD/NEWS                      |    9 
 robustHD-0.7.1/robustHD/R/AIC.R                   |  324 +++----
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 robustHD-0.7.1/robustHD/R/coef.R                  |  252 +++---
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 robustHD-0.7.1/robustHD/R/fastLasso.R             |  100 +-
 robustHD-0.7.1/robustHD/R/fitted.R                |  202 ++--
 robustHD-0.7.1/robustHD/R/grouplars.R             |  648 +++++++--------
 robustHD-0.7.1/robustHD/R/grplars.R               |  750 ++++++++---------
 robustHD-0.7.1/robustHD/R/initialSubsets.R        |  100 +-
 robustHD-0.7.1/robustHD/R/lambda0.R               |  222 ++---
 robustHD-0.7.1/robustHD/R/perry.R                 |  314 +++----
 robustHD-0.7.1/robustHD/R/predict.R               |  468 +++++------
 robustHD-0.7.1/robustHD/R/print.R                 |  374 ++++----
 robustHD-0.7.1/robustHD/R/regFun.R                |  114 +-
 robustHD-0.7.1/robustHD/R/residuals.R             |  342 ++++----
 robustHD-0.7.1/robustHD/R/rlars.R                 |  696 ++++++++--------
 robustHD-0.7.1/robustHD/R/seqModel.R              |  212 ++---
 robustHD-0.7.1/robustHD/R/setupCoefPlot.R         |  570 ++++++-------
 robustHD-0.7.1/robustHD/R/setupCritPlot.R         |  468 +++++------
 robustHD-0.7.1/robustHD/R/setupDiagnosticPlot.R   |  918 +++++++++++-----------
 robustHD-0.7.1/robustHD/R/sparseLTS.R             |   19 
 robustHD-0.7.1/robustHD/R/standardize.R           |  260 +++---
 robustHD-0.7.1/robustHD/R/test.R                  |   62 -
 robustHD-0.7.1/robustHD/R/tsBlocks.R              |  180 ++--
 robustHD-0.7.1/robustHD/R/tslars.R                |  644 +++++++--------
 robustHD-0.7.1/robustHD/R/tslarsP.R               |  608 +++++++-------
 robustHD-0.7.1/robustHD/R/utils.R                 |  508 ++++++------
 robustHD-0.7.1/robustHD/R/weights.R               |  116 +-
 robustHD-0.7.1/robustHD/R/winsorize.R             |  384 ++++-----
 robustHD-0.7.1/robustHD/build/partial.rdb         |binary
 robustHD-0.7.1/robustHD/man/AIC.seqModel.Rd       |  216 ++---
 robustHD-0.7.1/robustHD/man/TopGear.Rd            |  152 +--
 robustHD-0.7.1/robustHD/man/coef.seqModel.Rd      |  230 ++---
 robustHD-0.7.1/robustHD/man/corHuber.Rd           |  226 ++---
 robustHD-0.7.1/robustHD/man/fitted.seqModel.Rd    |  222 ++---
 robustHD-0.7.1/robustHD/man/getScale.Rd           |  138 +--
 robustHD-0.7.1/robustHD/man/grplars.Rd            |  542 ++++++------
 robustHD-0.7.1/robustHD/man/lambda0.Rd            |  224 ++---
 robustHD-0.7.1/robustHD/man/nci60.Rd              |  111 +-
 robustHD-0.7.1/robustHD/man/partialOrder.Rd       |   84 +-
 robustHD-0.7.1/robustHD/man/perry.seqModel.Rd     |  286 +++---
 robustHD-0.7.1/robustHD/man/plot.seqModel.Rd      |  190 ++--
 robustHD-0.7.1/robustHD/man/predict.seqModel.Rd   |  242 ++---
 robustHD-0.7.1/robustHD/man/residuals.seqModel.Rd |  230 ++---
 robustHD-0.7.1/robustHD/man/rlars.Rd              |  474 +++++------
 robustHD-0.7.1/robustHD/man/robustHD-package.Rd   |   44 -
 robustHD-0.7.1/robustHD/man/sparseLTS.Rd          |  585 +++++++-------
 robustHD-0.7.1/robustHD/man/standardize.Rd        |  152 +--
 robustHD-0.7.1/robustHD/man/tsBlocks.Rd           |   82 -
 robustHD-0.7.1/robustHD/man/tslars.Rd             |  402 ++++-----
 robustHD-0.7.1/robustHD/man/tslarsP.Rd            |  456 +++++-----
 robustHD-0.7.1/robustHD/man/weights.sparseLTS.Rd  |  172 ++--
 robustHD-0.7.1/robustHD/man/winsorize.Rd          |  250 ++---
 robustHD-0.7.1/robustHD/tests                     |only
 58 files changed, 8204 insertions(+), 8179 deletions(-)

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New package pvcurveanalysis with initial version 1.0.0
Package: pvcurveanalysis
Title: Analysis of Pressure Volume Curves
Version: 1.0.0
Depends: ggplot2, R (>= 3.5.0)
Suggests: knitr, rmarkdown
VignetteBuilder: knitr
Description: Enables the manufacturing, analysis and display of pressure volume curves. From the progression of the curves, turgor loss point, osmotic potential and apoplastic fraction can be derived. Methods adapted from Bartlett, Scoffoni and Sack (2012) <doi:10.1111/j.1461-0248.2012.01751.x>.
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
NeedsCompilation: no
Packaged: 2021-10-12 16:17:09 UTC; anna.raesch
Author: Anna Raesch [aut, cre, cph]
Maintainer: Anna Raesch <annaraesch@gmail.com>
Repository: CRAN
Date/Publication: 2021-10-13 10:00:02 UTC

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New package KingCountyHouses with initial version 0.1.0
Package: KingCountyHouses
Title: Data on House Sales in King County WA
Version: 0.1.0
Description: Data on houses in and around Seattle WA are included. Basic characteristics are given along with sale prices.
License: MIT + file LICENSE
Encoding: UTF-8
Suggests: spelling
Language: en-US
Depends: R (>= 2.10)
LazyData: true
NeedsCompilation: no
Packaged: 2021-10-12 19:37:28 UTC; max
Author: Max Kuhn [aut, cre] (<https://orcid.org/0000-0003-2402-136X>)
Maintainer: Max Kuhn <max@rstudio.com>
Repository: CRAN
Date/Publication: 2021-10-13 10:00:08 UTC

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New package hydropeak with initial version 0.1.0
Package: hydropeak
Title: Detect and Characterize Sub-Daily Flow Fluctuations
Version: 0.1.0
Description: An important environmental impact on running water ecosystems is caused by hydropeaking - the discontinuous release of turbine water because of peaks of energy demand. An event-based algorithm is implemented to detect flow fluctuations referring to increase events (IC) and decrease events (DC). For each event, a set of parameters related to the fluctuation intensity is calculated: maximum flow fluctuation rate mafr(), mean flow fluctuation rate mefr(), amplitude amp(), flow ratio fr(), and duration dur(). The framework is introduced in Greimel et al. (2016) "A method to detect and characterize sub-daily flow fluctuations" <doi:10.1002/hyp.10773> and can be used to identify different fluctuation types according to the potential source: e.g., sub-daily flow fluctuations caused by hydropeaking, rainfall, or snow and glacier melt.
License: GPL-2
Encoding: UTF-8
LazyData: true
Depends: R (>= 3.5.0)
Suggests: rmarkdown, knitr, testthat (>= 3.0.0), data.table
Imports: utils, parallel
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2021-10-12 14:05:58 UTC; gruen
Author: Bettina Grün [cre, ctb] (<https://orcid.org/0000-0001-7265-4773>), Julia Haider [aut], Franz Greimel [ctb] (<https://orcid.org/0000-0002-8000-1227>)
Maintainer: Bettina Grün <Bettina.Gruen@R-project.org>
Repository: CRAN
Date/Publication: 2021-10-13 10:00:05 UTC

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Package hhsmm updated to version 0.2.0 with previous version 0.1.3 dated 2021-09-13

Title: Hidden Hybrid Markov/Semi-Markov Model Fitting
Description: Develops algorithms for fitting, prediction, simulation and initialization of the hidden hybrid Markov/semi-Markov model, introduced by Guedon (2005) <doi:10.1016/j.csda.2004.05.033>.
Author: Morteza Amini [aut, cre, cph], Afarin Bayat [aut]
Maintainer: Morteza Amini <morteza.amini@ut.ac.ir>

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Package HelpersMG updated to version 4.8 with previous version 4.7-0 dated 2021-09-02

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

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Package textTinyR updated to version 1.1.5 with previous version 1.1.4 dated 2021-05-05

Title: Text Processing for Small or Big Data Files
Description: It offers functions for splitting, parsing, tokenizing and creating a vocabulary for big text data files. Moreover, it includes functions for building a document-term matrix and extracting information from those (term-associations, most frequent terms). It also embodies functions for calculating token statistics (collocations, look-up tables, string dissimilarities) and functions to work with sparse matrices. Lastly, it includes functions for Word Vector Representations (i.e. 'GloVe', 'fasttext') and incorporates functions for the calculation of (pairwise) text document dissimilarities. The source code is based on 'C++11' and exported in R through the 'Rcpp', 'RcppArmadillo' and 'BH' packages.
Author: Lampros Mouselimis [aut, cre] (<https://orcid.org/0000-0002-8024-1546>)
Maintainer: Lampros Mouselimis <mouselimislampros@gmail.com>

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Package elo (with last version 2.1.1) was removed from CRAN

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

2020-01-14 2.1.1
2019-08-02 2.0.0
2019-01-21 1.1.0
2017-12-14 1.0.1
2017-11-20 1.0.0
2017-08-16 0.1.2

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Package popEpi (with last version 0.4.8) was removed from CRAN

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

2019-09-28 0.4.8
2019-03-18 0.4.7
2019-02-14 0.4.6
2018-05-16 0.4.5
2017-11-14 0.4.4
2017-09-05 0.4.3
2017-08-10 0.4.2
2016-11-08 0.4.1
2016-09-23 0.4.0
2016-04-25 0.3.1
2016-03-31 0.3.0
2015-09-29 0.2.1

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Package permutes updated to version 2.2 with previous version 2.1.1 dated 2021-09-14

Title: Permutation Tests for Time Series Data
Description: Helps you determine the analysis window to use when analyzing densely-sampled time-series data, such as EEG data, using permutation testing (Maris & Oostenveld, 2007) <doi:10.1016/j.jneumeth.2007.03.024>. These permutation tests can help identify the timepoints where significance of an effect begins and ends, and the results can be plotted in various types of heatmap for reporting. Mixed-effects models are supported using an implementation of the approach by Lee & Braun (2012) <doi:10.1111/j.1541-0420.2011.01675.x>.
Author: Cesko C. Voeten [aut, cre]
Maintainer: Cesko C. Voeten <cvoeten@gmail.com>

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Package soilphysics (with last version 4.0) was removed from CRAN

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

2020-12-07 4.0
2017-05-25 3.1
2016-01-11 3.0
2015-06-26 2.4
2015-05-09 2.3
2015-04-10 2.2
2015-03-11 2.1
2015-01-11 2.0
2014-10-14 1.2
2014-07-17 1.1
2014-01-25 1.0

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Package seedwater (with last version 2.0) was removed from CRAN

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

2020-12-04 2.0
2019-02-12 1.0

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Package AgroR (with last version 1.2.3) was removed from CRAN

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

2021-09-03 1.2.3
2021-07-16 1.2.2
2021-06-24 1.2.1
2021-06-14 1.2.0
2021-05-28 1.1.0
2021-05-18 1.0.0

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Package jsr223 (with last version 0.3.4) was removed from CRAN

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

2020-06-04 0.3.4
2018-12-12 0.3.3
2018-04-30 0.3.2
2018-04-05 0.3.1
2018-03-13 0.3.0

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Package sitmo updated to version 2.0.2 with previous version 2.0.1 dated 2019-01-07

Title: Parallel Pseudo Random Number Generator (PPRNG) 'sitmo' Header Files
Description: Provided within are two high quality and fast PPRNGs that may be used in an 'OpenMP' parallel environment. In addition, there is a generator for one dimensional low-discrepancy sequence. The objective of this library to consolidate the distribution of the 'sitmo' (C++98 & C++11), 'threefry' and 'vandercorput' (C++11-only) engines on CRAN by enabling others to link to the header files inside of 'sitmo' instead of including a copy of each engine within their individual package. Lastly, the package contains example implementations using the 'sitmo' package and three accompanying vignette that provide additional information.
Author: James Balamuta [aut, cre, cph] (<https://orcid.org/0000-0003-2826-8458>), Thijs van den Berg [aut, cph], Ralf Stubner [ctb]
Maintainer: James Balamuta <balamut2@illinois.edu>

Diff between sitmo versions 2.0.1 dated 2019-01-07 and 2.0.2 dated 2021-10-13

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Package netmeta updated to version 2.0-0 with previous version 1.5-0 dated 2021-06-29

Title: Network Meta-Analysis using Frequentist Methods
Description: A comprehensive set of functions providing frequentist methods for network meta-analysis and supporting Schwarzer et al. (2015) <DOI:10.1007/978-3-319-21416-0>, Chapter 8 "Network Meta-Analysis": - frequentist network meta-analysis following Rücker (2012) <DOI:10.1002/jrsm.1058>; - net heat plot and design-based decomposition of Cochran's Q according to Krahn et al. (2013) <DOI:10.1186/1471-2288-13-35>; - measures characterizing the flow of evidence between two treatments by König et al. (2013) <DOI:10.1002/sim.6001>; - ranking of treatments (frequentist analogue of SUCRA) according to Rücker & Schwarzer (2015) <DOI:10.1186/s12874-015-0060-8>; - partial order of treatment rankings ('poset') and Hasse diagram for 'poset' (Carlsen & Bruggemann, 2014) <DOI:10.1002/cem.2569>; (Rücker & Schwarzer, 2017) <DOI:10.1002/jrsm.1270>; - split direct and indirect evidence to check consistency (Dias et al., 2010) <DOI:10.1002/sim.3767>, (Efthimiou et al., 2019) <DOI:10.1002/sim.8158>; - league table with network meta-analysis results; - additive network meta-analysis for combinations of treatments (Rücker et al., 2020) <DOI:10.1002/bimj.201800167>; - network meta-analysis of binary data using the Mantel-Haenszel or non-central hypergeometric distribution method (Efthimiou et al., 2019) <DOI:10.1002/sim.8158>; - 'comparison-adjusted' funnel plot (Chaimani & Salanti, 2012) <DOI:10.1002/jrsm.57>; - automated drawing of network graphs described in Rücker & Schwarzer (2016) <DOI:10.1002/jrsm.1143>; - rankograms and ranking by SUCRA; - contribution matrix as described in Papakonstantinou et al. (2018) <DOI:10.12688/f1000research.14770.3> and Davies et al. (2021) <arXiv:2107.02886>.
Author: Gerta Rücker [aut] (<https://orcid.org/0000-0002-2192-2560>), Ulrike Krahn [aut], Jochem König [aut] (<https://orcid.org/0000-0003-4683-0360>), Orestis Efthimiou [aut] (<https://orcid.org/0000-0002-0955-7572>), Annabel Davies [aut] (<https://orcid.org/0000-0003-2320-7701>), Theodoros Papakonstantinou [aut] (<https://orcid.org/0000-0002-6630-6817>), Guido Schwarzer [aut, cre] (<https://orcid.org/0000-0001-6214-9087>)
Maintainer: Guido Schwarzer <sc@imbi.uni-freiburg.de>

Diff between netmeta versions 1.5-0 dated 2021-06-29 and 2.0-0 dated 2021-10-13

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More information about netmeta at CRAN
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Package BEST updated to version 0.5.4 with previous version 0.5.3 dated 2021-05-17

Title: Bayesian Estimation Supersedes the t-Test
Description: An alternative to t-tests, producing posterior estimates for group means and standard deviations and their differences and effect sizes. It implements the method of Kruschke (2013) Bayesian estimation supersedes the t test. Journal of Experimental Psychology: General, 142(2):573-603 <doi: 10.1037/a0029146>.
Author: John Kruschke [aut], Mike Meredith [aut, cre]
Maintainer: Mike Meredith <mike@mmeredith.net>

Diff between BEST versions 0.5.3 dated 2021-05-17 and 0.5.4 dated 2021-10-13

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 22 files changed, 213 insertions(+), 108 deletions(-)

More information about BEST at CRAN
Permanent link


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