Thu, 22 Apr 2021

Package LPRelevance updated to version 3.2 with previous version 3.1 dated 2020-05-16

Title: Relevance-Integrated Statistical Inference Engine
Description: Provide methods to perform customized inference at individual level by taking contextual covariates into account. Three main functions are provided in this package: (i) LASER(): it generates specially-designed artificial relevant samples for a given case; (ii) g2l.proc(): computes customized fdr(z|x); and (iii) rEB.proc(): performs empirical Bayes inference based on LASERs. The details can be found in Mukhopadhyay, S., and Wang, K (2021, <arXiv:2004.09588>).
Author: Subhadeep Mukhopadhyay, Kaijun Wang
Maintainer: Kaijun Wang <kaijunwang.19@gmail.com>

Diff between LPRelevance versions 3.1 dated 2020-05-16 and 3.2 dated 2021-04-22

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More information about LPRelevance at CRAN
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Package dmutate updated to version 0.1.3 with previous version 0.1.2 dated 2017-08-28

Title: Mutate Data Frames with Random Variates
Description: Work within the 'dplyr' workflow to add random variates to your data frame. Variates can be added at any level of an existing column. Also, bounds can be specified for simulated variates.
Author: Kyle T Baron [aut, cre, cph]
Maintainer: Kyle T Baron <kylebtwin@imap.cc>

Diff between dmutate versions 0.1.2 dated 2017-08-28 and 0.1.3 dated 2021-04-22

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More information about dmutate at CRAN
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Package xgxr updated to version 1.1.1 with previous version 1.1.0 dated 2021-02-04

Title: Exploratory Graphics for Pharmacometrics
Description: Supports a structured approach for exploring PKPD data <https://opensource.nibr.com/xgx/>. It also contains helper functions for enabling the modeler to follow best R practices (by appending the program name, figure name location, and draft status to each plot). In addition, it enables the modeler to follow best graphical practices (by providing a theme that reduces chart ink, and by providing time-scale, log-scale, and reverse-log-transform-scale functions for more readable axes). Finally, it provides some data checking and summarizing functions for rapidly exploring pharmacokinetics and pharmacodynamics (PKPD) datasets.
Author: Andrew Stein [aut, cre], Alison Margolskee [aut], Fariba Khanshan [aut], Konstantin Krismer [aut] (<https://orcid.org/0000-0001-8994-3416>), Matthew Fidler [ctb] (<https://orcid.org/0000-0001-8538-6691>), Novartis Pharma AG [cph, fnd]
Maintainer: Andrew Stein <andy.stein@gmail.com>

Diff between xgxr versions 1.1.0 dated 2021-02-04 and 1.1.1 dated 2021-04-22

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More information about xgxr at CRAN
Permanent link

Package targets updated to version 0.4.1 with previous version 0.3.1 dated 2021-03-28

Title: Dynamic Function-Oriented 'Make'-Like Declarative Workflows
Description: As a pipeline toolkit for Statistics and data science in R, the 'targets' package brings together function-oriented programming and 'Make'-like declarative workflows. It analyzes the dependency relationships among the tasks of a workflow, skips steps that are already up to date, runs the necessary computation with optional parallel workers, abstracts files as R objects, and provides tangible evidence that the results match the underlying code and data. The methodology in this package borrows from GNU 'Make' (2015, ISBN:978-9881443519) and 'drake' (2018, <doi:10.21105/joss.00550>).
Author: William Michael Landau [aut, cre] (<https://orcid.org/0000-0003-1878-3253>), Matthew T. Warkentin [ctb], Samantha Oliver [rev] (<https://orcid.org/0000-0001-5668-1165>), Tristan Mahr [rev] (<https://orcid.org/0000-0002-8890-5116>), Eli Lilly and Company [cph]
Maintainer: William Michael Landau <will.landau@gmail.com>

Diff between targets versions 0.3.1 dated 2021-03-28 and 0.4.1 dated 2021-04-22

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Package cronologia updated to version 0.2.0 with previous version 0.1.0 dated 2021-02-07

Title: Create an HTML Vertical Timeline from a Data Frame in 'rmarkdown' and 'shiny'
Description: Creates an HTML vertical timeline from a data frame as an input for 'rmarkdown' documents and 'shiny' applications.
Author: Mohamed El Fodil Ihaddaden
Maintainer: Mohamed El Fodil Ihaddaden <ihaddaden.fodeil@gmail.com>

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Package clock updated to version 0.3.0 with previous version 0.2.0 dated 2021-04-12

Title: Date-Time Types and Tools
Description: Provides a comprehensive library for date-time manipulations using a new family of orthogonal date-time classes (durations, time points, zoned-times, and calendars) that partition responsibilities so that the complexities of time zones are only considered when they are really needed. Capabilities include: date-time parsing, formatting, arithmetic, extraction and updating of components, and rounding.
Author: Davis Vaughan [aut, cre], RStudio [cph, fnd]
Maintainer: Davis Vaughan <davis@rstudio.com>

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Package BHSBVAR updated to version 3.0.0 with previous version 2.1.0 dated 2020-08-26

Title: Structural Bayesian Vector Autoregression Models
Description: Provides a function for estimating the parameters of Structural Bayesian Vector Autoregression models with the method developed by Baumeister and Hamilton (2015) <doi:10.3982/ECTA12356>, Baumeister and Hamilton (2017) <doi:10.3386/w24167>, and Baumeister and Hamilton (2018) <doi:10.1016/j.jmoneco.2018.06.005>. Functions for plotting impulse responses, historical decompositions, and posterior distributions of model parameters are also provided.
Author: Paul Richardson
Maintainer: Paul Richardson <p.richardson.54391@gmail.com>

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Package mrbin updated to version 1.5.1 with previous version 1.5.0 dated 2021-01-04

Title: Magnetic Resonance Binning, Integration and Normalization
Description: Nuclear Magnetic Resonance is widely used in Life Science research. The package (<doi:10.1021/acs.jproteome.0c00684>) converts 1D or 2D data into a matrix of values suitable for further data analysis and performs basic processing steps in a reproducible way. Negative values, a common issue in such data, are replaced by positive values. All used parameters are stored in a readable text file and can be restored from that file to enable exact reproduction of the data at a later time.
Author: Matthias Klein [aut, cre] (<https://orcid.org/0000-0001-7455-5381>)
Maintainer: Matthias Klein <klein.663@osu.edu>

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Package drake updated to version 7.13.2 with previous version 7.13.1 dated 2021-02-03

Title: A Pipeline Toolkit for Reproducible Computation at Scale
Description: A general-purpose computational engine for data analysis, drake rebuilds intermediate data objects when their dependencies change, and it skips work when the results are already up to date. Not every execution starts from scratch, there is native support for parallel and distributed computing, and completed projects have tangible evidence that they are reproducible. Extensive documentation, from beginner-friendly tutorials to practical examples and more, is available at the reference website <https://docs.ropensci.org/drake/> and the online manual <https://books.ropensci.org/drake/>.
Author: William Michael Landau [aut, cre] (<https://orcid.org/0000-0003-1878-3253>), Alex Axthelm [ctb], Jasper Clarkberg [ctb], Kirill Müller [ctb], Ben Bond-Lamberty [ctb] (<https://orcid.org/0000-0001-9525-4633>), Tristan Mahr [ctb] (<https://orcid.org/0000-0002-8890-5116>), Miles McBain [ctb] (<https://orcid.org/0000-0003-2865-2548>), Noam Ross [ctb] (<https://orcid.org/0000-0002-2136-0000>), Ellis Hughes [ctb], Matthew Mark Strasiotto [ctb], Ben Marwick [rev], Peter Slaughter [rev], Eli Lilly and Company [cph]
Maintainer: William Michael Landau <will.landau@gmail.com>

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Package IalsaSynthesis (with last version 0.1.6) was removed from CRAN

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

2015-09-02 0.1.6

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Package NlsyLinks (with last version 2.0.6) was removed from CRAN

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

2016-04-19 2.0.6
2015-08-18 2.0.1
2013-12-06 1.302
2013-11-27 1.300
2012-12-19 1.200
2012-05-21 1.003
2012-04-27 1.0
2012-03-10 0.19
2012-01-16 0.10

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Package RSQLite updated to version 2.2.7 with previous version 2.2.6 dated 2021-04-11

Title: 'SQLite' Interface for R
Description: Embeds the 'SQLite' database engine in R and provides an interface compliant with the 'DBI' package. The source for the 'SQLite' engine is included.
Author: Kirill Müller [aut, cre] (<https://orcid.org/0000-0002-1416-3412>), Hadley Wickham [aut], David A. James [aut], Seth Falcon [aut], SQLite Authors [ctb] (for the included SQLite sources), Liam Healy [ctb] (for the included SQLite sources), R Consortium [fnd], RStudio [cph]
Maintainer: Kirill Müller <krlmlr+r@mailbox.org>

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Package randomNames updated to version 1.5-0.0 with previous version 1.4-0.0 dated 2019-03-07

Title: Generate Random Given and Surnames
Description: Function for generating random gender and ethnicity correct first and/or last names. Names are chosen proportionally based upon their probability of appearing in a large scale data base of real names.
Author: Damian W. Betebenner [aut, cre]
Maintainer: Damian W. Betebenner <dbetebenner@nciea.org>

Diff between randomNames versions 1.4-0.0 dated 2019-03-07 and 1.5-0.0 dated 2021-04-22

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New package RAMClustR with initial version 1.2.0
Package: RAMClustR
Title: Mass Spectrometry Metabolomics Feature Clustering and Interpretation
Version: 1.2.0
Date: 2021-04-19
Author: Corey D. Broeckling, Fayyaz Afsar, Steffan Neumann, Asa Ben-Hur, Jessica Prenni.
Maintainer: "Broeckling,Corey" <Corey.Broeckling@ColoState.EDU>
Imports: dynamicTreeCut, fastcluster, ff, InterpretMSSpectrum, BiocManager, httr, jsonlite, preprocessCore, e1071, gplots, pcaMethods, stringr, xml2, utils, webchem, stringi, RCurl, MSnbase, ggplot2
License: GPL (>= 2)
Description: A feature clustering algorithm for non-targeted mass spectrometric metabolomics data. This method is compatible with gas and liquid chromatography coupled mass spectrometry, including indiscriminant tandem mass spectrometry <DOI: 10.1021/ac501530d> data.
URL: https://github.com/cbroeckl/RAMClustR
Encoding: UTF-8
biocViews: MassSpectrometry, Metabolomics
Suggests: knitr, rmarkdown, xcms
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2021-04-20 15:39:35 UTC; cbroe
Repository: CRAN
Date/Publication: 2021-04-22 15:20:02 UTC

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Package BaseSet updated to version 0.0.16 with previous version 0.0.15 dated 2021-03-20

Title: Working with Sets the Tidy Way
Description: Implements a class and methods to work with sets, doing intersection, union, complementary sets, power sets, cartesian product and other set operations in a "tidy" way. These set operations are available for both classical sets and fuzzy sets. Import sets from several formats or from other several data structures.
Author: Lluís Revilla Sancho [aut, cre] (<https://orcid.org/0000-0001-9747-2570>), Zebulun Arendsee [rev], Jennifer Chang [rev]
Maintainer: Lluís Revilla Sancho <lluis.revilla@gmail.com>

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Package ukbabynames updated to version 0.2.0 with previous version 0.1.1 dated 2017-06-20

Title: UK Baby Names Data
Description: Full listing of UK baby names occurring more than three times per year between 1974 and 2020, and rankings of baby name popularity by decade from 1904 to 1994.
Author: Mine Çetinkaya-Rundel [aut, cre, cph] (<https://orcid.org/0000-0001-6452-2420>), Thomas J. Leeper [aut], Nicholas Goguen-Compagnoni [aut]
Maintainer: Mine Çetinkaya-Rundel <cetinkaya.mine@gmail.com>

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Package TSEtools updated to version 0.2.1 with previous version 0.2.0 dated 2021-01-24

Title: Manage Data from Stock Exchange Markets
Description: Tools to perform some descriptive data analysis for assets. Manage the portfolio and capital of assets. It also downloads and organizes data from the Tehran Stock Exchange (TSE).
Author: Ali Saeb
Maintainer: Ali Saeb <ali.saeb@gmail.com>

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Package tensorTS updated to version 0.1.1 with previous version 0.1.0 dated 2021-04-21

Title: Factor and Autoregressive Models for Tensor Time Series
Description: Factor and autoregressive models for matrix and tensor valued time series. We provide functions for estimation, simulation and prediction. The models are discussed in Chen et al (2020) <DOI:10.1016/j.jeconom.2020.07.015>, Chen et al (2020) <arXiv:1905.07530>, and Han et al (2020) <arXiv:2006.02611>.
Author: Zebang Li [aut, cre], Ruofan Yu [aut], Rong Chen [aut], Yuefeng Han [aut], Han Xiao [aut], Dan Yang [aut]
Maintainer: Zebang Li <zl326@stat.rutgers.edu>

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Package stagedtrees updated to version 2.1.0 with previous version 2.0.1 dated 2020-12-08

Title: Staged Event Trees
Description: Creates and fits staged event tree probability models, which are probabilistic graphical models capable of representing asymmetric conditional independence statements for categorical variables. Includes functions to create, plot and fit staged event trees from data, as well as many efficient structure learning algorithms. References: Collazo R. A., Görgen C. and Smith J. Q. (2018, ISBN:9781498729604). Görgen C., Bigatti A., Riccomagno E. and Smith J. Q. (2018) <arXiv:1705.09457>. Thwaites P. A., Smith, J. Q. (2017) <arXiv:1510.00186>. Barclay L. M., Hutton J. L. and Smith J. Q. (2013) <doi:10.1016/j.ijar.2013.05.006>. Smith J. Q. and Anderson P. E. (2008) <doi:10.1016/j.artint.2007.05.004>.
Author: Gherardo Varando [aut, cre] (<https://orcid.org/0000-0002-6708-1103>), Federico Carli [aut], Manuele Leonelli [aut] (<https://orcid.org/0000-0002-2562-5192>), Eva Riccomagno [aut]
Maintainer: Gherardo Varando <gherardo.varando@gmail.com>

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Package sitar updated to version 1.2.0 with previous version 1.1.2 dated 2020-02-17

Title: Super Imposition by Translation and Rotation Growth Curve Analysis
Description: Functions for fitting and plotting SITAR (Super Imposition by Translation And Rotation) growth curve models. SITAR is a shape-invariant model with a regression B-spline mean curve and subject-specific random effects on both the measurement and age scales. The model was first described by Lindstrom (1995) <doi:10.1002/sim.4780141807> and developed as the SITAR method by Cole et al (2010) <doi:10.1093/ije/dyq115>.
Author: Tim Cole [aut, cre] (<https://orcid.org/0000-0001-5711-8200>)
Maintainer: Tim Cole <tim.cole@ucl.ac.uk>

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Package rslurm updated to version 0.6.0 with previous version 0.5.0 dated 2019-11-15

Title: Submit R Calculations to a 'Slurm' Cluster
Description: Functions that simplify submitting R scripts to a 'Slurm' workload manager, in part by automating the division of embarrassingly parallel calculations across cluster nodes.
Author: Philippe Marchand [aut], Ian Carroll [aut], Mike Smorul [aut], Rachael Blake [aut], Quentin Read [aut, cre], Dayne Filer [ctb], Ben Fasoli [ctb], Pol van Rijn [ctb], Sebastian Schubert [ctb], Rob Gilmore [ctb], Christopher Barrington [ctb], Se Jong Cho [art]
Maintainer: Quentin Read <qread@sesync.org>

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Package provDebugR updated to version 1.0.1 with previous version 1.0 dated 2021-02-17

Title: A Time-Travelling Debugger
Description: Uses provenance post-execution to help the user understand and debug their script by providing functions to look at intermediate steps and data values, their forwards and backwards lineage, and to understand the steps leading up to warning and error messages. 'provDebugR' uses provenance produced by 'rdtLite' (available on CRAN), stored in PROV-JSON format.
Author: Orenna Brand [aut], Elizabeth Fong [aut], Barbara Lerner [cre], Rose Sheehan [aut], Joseph Wonsil [aut], Emery Boose [aut]
Maintainer: Barbara Lerner <blerner@mtholyoke.edu>

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Package iSubGen updated to version 1.0.1 with previous version 1.0.0 dated 2021-04-15

Title: Integrative Subtype Generation
Description: Multi-data type subtyping, which is data type agnostic and accepts missing data. Subtyping is performed using intermediary assessments created with autoencoders and similarity calculations.
Author: Natalie Fox
Maintainer: Paul C Boutros <pboutros@mednet.ucla.edu>

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Package experDesign updated to version 0.1.0 with previous version 0.0.4 dated 2020-09-28

Title: Design Experiments for Batches
Description: Distributes samples in batches while making batches homogeneous according to their description. Allows for an arbitrary number of variables, both numeric and categorical. For quality control it provides functions to subset a representative sample.
Author: Lluís Revilla Sancho [aut, cre] (<https://orcid.org/0000-0001-9747-2570>)
Maintainer: Lluís Revilla Sancho <lluis.revilla@gmail.com>

Diff between experDesign versions 0.0.4 dated 2020-09-28 and 0.1.0 dated 2021-04-22

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Package detectseparation updated to version 0.2 with previous version 0.1 dated 2020-03-25

Title: Detect and Check for Separation and Infinite Maximum Likelihood Estimates
Description: Provides pre-fit and post-fit methods for detecting separation and infinite maximum likelihood estimates in generalized linear models with categorical responses. The pre-fit methods apply on binomial-response generalized liner models such as logit, probit and cloglog regression, and can be directly supplied as fitting methods to the glm() function. They solve the linear programming problems for the detection of separation developed in Konis (2007, <https://ora.ox.ac.uk/objects/uuid:8f9ee0d0-d78e-4101-9ab4-f9cbceed2a2a>) using 'ROI' <https://cran.r-project.org/package=ROI> or 'lpSolveAPI' <https://cran.r-project.org/package=lpSolveAPI>. The post-fit methods apply to models with categorical responses, including binomial-response generalized linear models and multinomial-response models, such as baseline category logits and adjacent category logits models; for example, the models implemented in the 'brglm2' <https://cran.r-project.org/package=brglm2> package. The post-fit methods successively refit the model with increasing number of iteratively reweighted least squares iterations, and monitor the ratio of the estimated standard error for each parameter to what it has been in the first iteration. According to the results in Lesaffre & Albert (1989, <https://www.jstor.org/stable/2345845>), divergence of those ratios indicates data separation.
Author: Ioannis Kosmidis [aut, cre] (<https://orcid.org/0000-0003-1556-0302>), Dirk Schumacher [aut], Kjell Konis [ctb]
Maintainer: Ioannis Kosmidis <ioannis.kosmidis@warwick.ac.uk>

Diff between detectseparation versions 0.1 dated 2020-03-25 and 0.2 dated 2021-04-22

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Package CatReg updated to version 2.0.2 with previous version 2.0.1 dated 2020-11-14

Title: Solution Paths for Linear and Logistic Regression Models with Categorical Predictors, with SCOPE Penalty
Description: Computes solutions for linear and logistic regression models with potentially high-dimensional categorical predictors. This is done by applying a nonconvex penalty (SCOPE) and computing solutions in an efficient path-wise fashion. The scaling of the solution paths is selected automatically. Includes functionality for selecting tuning parameter lambda by k-fold cross-validation and early termination based on information criteria. Solutions are computed by cyclical block-coordinate descent, iterating an innovative dynamic programming algorithm to compute exact solutions for each block.
Author: Benjamin Stokell [aut], Daniel Grose [ctb, cre], Rajen Shah [ctb]
Maintainer: Daniel Grose <dan.grose@lancaster.ac.uk>

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Package bayesGARCH updated to version 2.1.8 with previous version 2.1.7 dated 2021-04-20

Title: Bayesian Estimation of the GARCH(1,1) Model with Student-t Innovations
Description: Provides the bayesGARCH() function which performs the Bayesian estimation of the GARCH(1,1) model with Student's t innovations as described in Ardia (2008) <doi:10.1007/978-3-540-78657-3>.
Author: David Ardia [aut, cre, cph] (<https://orcid.org/0000-0003-2823-782X>)
Maintainer: David Ardia <david.ardia.ch@gmail.com>

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Package TAM updated to version 3.6-45 with previous version 3.5-19 dated 2020-05-06

Title: Test Analysis Modules
Description: Includes marginal maximum likelihood estimation and joint maximum likelihood estimation for unidimensional and multidimensional item response models. The package functionality covers the Rasch model, 2PL model, 3PL model, generalized partial credit model, multi-faceted Rasch model, nominal item response model, structured latent class model, mixture distribution IRT models, and located latent class models. Latent regression models and plausible value imputation are also supported. For details see Adams, Wilson and Wang, 1997 <doi:10.1177/0146621697211001>, Adams, Wilson and Wu, 1997 <doi:10.3102/10769986022001047>, Formann, 1982 <doi:10.1002/bimj.4710240209>, Formann, 1992 <doi:10.1080/01621459.1992.10475229>.
Author: Alexander Robitzsch [aut,cre] (<https://orcid.org/0000-0002-8226-3132>), Thomas Kiefer [aut], Margaret Wu [aut]
Maintainer: Alexander Robitzsch <robitzsch@ipn.uni-kiel.de>

Diff between TAM versions 3.5-19 dated 2020-05-06 and 3.6-45 dated 2021-04-22

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Package segmented updated to version 1.3-4 with previous version 1.3-3 dated 2021-03-08

Title: Regression Models with Break-Points / Change-Points Estimation
Description: Given a regression model, segmented `updates' it by adding one or more segmented (i.e., piece-wise linear) relationships. Several variables with multiple breakpoints are allowed. The estimation method is discussed in Muggeo (2003, <doi:10.1002/sim.1545>) and illustrated in Muggeo (2008, <https://www.r-project.org/doc/Rnews/Rnews_2008-1.pdf>). An approach for hypothesis testing is presented in Muggeo (2016, <doi:10.1080/00949655.2016.1149855>), and interval estimation for the breakpoint is discussed in Muggeo (2017, <doi:10.1111/anzs.12200>).
Author: Vito M. R. Muggeo [aut, cre] (<https://orcid.org/0000-0002-3386-4054>)
Maintainer: Vito M. R. Muggeo <vito.muggeo@unipa.it>

Diff between segmented versions 1.3-3 dated 2021-03-08 and 1.3-4 dated 2021-04-22

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Package qrandom updated to version 1.2.4 with previous version 1.2.3 dated 2020-09-08

Title: True Random Numbers using the ANU Quantum Random Numbers Server
Description: The ANU Quantum Random Number Generator provided by the Australian National University generates true random numbers in real-time by measuring the quantum fluctuations of the vacuum. This package offers an interface using their API. The electromagnetic field of the vacuum exhibits random fluctuations in phase and amplitude at all frequencies. By carefully measuring these fluctuations, one is able to generate ultra-high bandwidth random numbers. The quantum Random Number Generator is based on the papers by Symul et al., (2011) <doi:10.1063/1.3597793> and Haw, et al. (2015) <doi:10.1103/PhysRevApplied.3.054004>. The package offers functions to retrieve a sequence of random integers or hexadecimals and true random samples from a normal or uniform distribution.
Author: Siegfried Köstlmeier [aut, cre] (<https://orcid.org/0000-0002-7221-6981>), Boris Steipe [ctb] (<https://orcid.org/0000-0002-1134-6758>)
Maintainer: Siegfried Köstlmeier <siegfried.koestlmeier@gmail.com>

Diff between qrandom versions 1.2.3 dated 2020-09-08 and 1.2.4 dated 2021-04-22

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Package mobirep updated to version 0.2.3 with previous version 0.2.2 dated 2021-04-20

Title: Models Bivariate Dependence and Produces Bivariate Return Periods
Description: Models the dependence between two variables in the extremes, identifies most relevant models among six models: the conditional extremes model, the Jt-KDE model and four copulae (Gumbel, Galambos, Normal, FGM). Bivariate return periods for the six models and bivariate level curves can be created. Methods used in the package are described in the following reference: Tilloy, Malamud, Winter and Joly-Laugel (2020) <doi:10.5194/nhess-20-2091-2020> Supporting references for the conditional extremes model, Jt-KDE model and for copula modelling are the following: Heffernan and Tawn (2004) <doi:10.1111/j.1467-9868.2004.02050.x> Cooley, Thibaud, Castillo and Wehner (2019) <doi:10.1007/s10687-019-00348-0> Nelsen (2006) <doi:10.1007/0-387-28678-0>.
Author: Alois Tilloy [aut, cre] (<https://orcid.org/0000-0002-5881-0642>)
Maintainer: Alois Tilloy <alois.tilloy@kcl.ac.uk>

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Package midasml updated to version 0.1.3 with previous version 0.1.2 dated 2021-04-21

Title: Estimation and Prediction Methods for High-Dimensional Mixed Frequency Time Series Data
Description: The 'midasml' package implements estimation and prediction methods for high-dimensional mixed-frequency (MIDAS) time-series and panel data regression models. The regularized MIDAS models are estimated using orthogonal (e.g. Legendre) polynomials and sparse-group LASSO (sg-LASSO) estimator. For more information on the `midasml' approach see Babii, Ghysels, and Striaukas (2021, JBES forthcoming) <doi:10.1080/07350015.2021.1899933>. The package is equipped with the fast implementation of the sg-LASSO estimator by means of proximal block coordinate descent. High-dimensional mixed frequency time-series data can also be easily manipulated with functions provided in the package.
Author: Jonas Striaukas [cre, aut], Andrii Babii [aut], Eric Ghysels [aut], Alex Kostrov [ctb] (Contributions to analytical gradients for non-linear low-dimensional MIDAS estimation code)
Maintainer: Jonas Striaukas <jonas.striaukas@gmail.com>

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Package ICSS updated to version 1.1 with previous version 1.0 dated 2020-06-02

Title: ICSS Algorithm by Inclan/Tiao (1994)
Description: The Iterative Cumulative Sum of Squares (ICSS) algorithm by Inclan/Tiao (1994) <https://www.jstor.org/stable/2290916> detects multiple change points, i.e. structural break points, in the variance of a sequence of independent observations. For series of moderate size (i.e. 200 observations and beyond), the ICSS algorithm offers results comparable to those obtained by a Bayesian approach or by likelihood ration tests, without the heavy computational burden required by these approaches.
Author: Siegfried Köstlmeier [aut, cre, cph] (<https://orcid.org/0000-0002-7221-6981>)
Maintainer: Siegfried Köstlmeier <siegfried.koestlmeier@gmail.com>

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Package dotenv updated to version 1.0.3 with previous version 1.0.2 dated 2017-03-01

Title: Load Environment Variables from '.env'
Description: Load configuration from a '.env' file, that is in the current working directory, into environment variables.
Author: Gábor Csárdi [aut, cre, cph]
Maintainer: Gábor Csárdi <csardi.gabor@gmail.com>

Diff between dotenv versions 1.0.2 dated 2017-03-01 and 1.0.3 dated 2021-04-22

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Package designr updated to version 0.1.12 with previous version 0.1.11 dated 2021-03-07

Title: Balanced Factorial Designs
Description: Generate balanced factorial designs with crossed and nested random and fixed effects <https://github.com/mmrabe/designr>.
Author: Maximilian M. Rabe [aut, cre] (<https://orcid.org/0000-0002-2556-5644>), Reinhold Kliegl [aut] (<https://orcid.org/0000-0002-0180-8488>), Daniel J. Schad [aut] (<https://orcid.org/0000-0003-2586-6823>)
Maintainer: Maximilian M. Rabe <maximilian.rabe@uni-potsdam.de>

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Package bookdown updated to version 0.22 with previous version 0.21 dated 2020-10-13

Title: Authoring Books and Technical Documents with R Markdown
Description: Output formats and utilities for authoring books and technical documents with R Markdown.
Author: Yihui Xie [aut, cre] (<https://orcid.org/0000-0003-0645-5666>), JJ Allaire [ctb], Albert Kim [ctb], Alessandro Samuel-Rosa [ctb], Andrzej Oles [ctb], Atsushi Yasumoto [ctb] (<https://orcid.org/0000-0002-8335-495X>), Aust Frederik [ctb] (<https://orcid.org/0000-0003-4900-788X>), Bastiaan Quast [ctb], Ben Marwick [ctb], Chester Ismay [ctb], Christophe Dervieux [ctb], Clifton Franklund [ctb], Daniel Emaasit [ctb], David Shuman [ctb], Dean Attali [ctb], Drew Tyre [ctb], Ellis Valentiner [ctb], Frans van Dunne [ctb], Hadley Wickham [ctb], Jeff Allen [ctb], Jennifer Bryan [ctb], Jonathan McPhers [ctb], JooYoung Seo [ctb] (<https://orcid.org/0000-0002-4064-6012>), Joyce Robbins [ctb], Junwen Huang [ctb], Kevin Cheung [ctb], Kevin Ushey [ctb], Kim Seonghyun [ctb], Kirill Muller [ctb], Luciano Selzer [ctb], Matthew Lincoln [ctb], Maximilian Held [ctb], Michael Sachs [ctb], Michal Bojanowski [ctb], Nathan Werth [ctb], Noam Ross [ctb], Peter Hickey [ctb], Pedro Rafael D. Marinho [ctb] (<https://orcid.org/0000-0003-1591-8300>), Romain Lesur [ctb] (<https://orcid.org/0000-0002-0721-5595>), Sahir Bhatnagar [ctb], Shir Dekel [ctb] (<https://orcid.org/0000-0003-1773-2446>), Steve Simpson [ctb], Thierry Onkelinx [ctb] (<https://orcid.org/0000-0001-8804-4216>), Vincent Fulco [ctb], Yixuan Qiu [ctb], Zhuoer Dong [ctb], RStudio, PBC [cph], Bartek Szopka [ctb] (The jQuery Highlight plugin), Zeno Rocha [cph] (clipboard.js library), jQuery Foundation [cph] (jQuery library), jQuery contributors [ctb, cph] (jQuery library; authors listed in inst/resources/AUTHORS), MathQuill contributors [ctb] (The MathQuill library; authors listed in inst/resources/AUTHORS), FriendCode Inc [cph, ctb] (The gitbook style, with modifications)
Maintainer: Yihui Xie <xie@yihui.name>

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Package od updated to version 0.2.1 with previous version 0.2.0 dated 2021-03-29

Title: Manipulate and Map Origin-Destination Data
Description: The aim of 'od' is to provide tools and example datasets for working with origin-destination ('OD') datasets of the type used to describe aggregate urban mobility patterns (Carey et al. 1981) <doi:10.1287/trsc.15.1.32>. The package builds on functions for working with 'OD' data in the package 'stplanr', (Lovelace and Ellison 2018) <doi:10.32614/RJ-2018-053> with a focus on computational efficiency and support for the 'sf' class system (Pebesma 2018) <doi:10.32614/RJ-2018-009>. With few dependencies and a simple class system based on data frames, the package is intended to facilitate efficient analysis of 'OD' datasets and to provide a place for developing new functions. The package enables the creation and analysis of geographic entities representing large scale mobility patterns, from daily travel between zones in cities to migration between countries.
Author: Robin Lovelace [aut, cre] (<https://orcid.org/0000-0001-5679-6536>), David Cooley [ctb]
Maintainer: Robin Lovelace <rob00x@gmail.com>

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Package neuromplex updated to version 1.0-1 with previous version 0.0-8 dated 2020-06-04

Title: Neural Multiplexing Analysis
Description: Statistical methods for whole-trial and time-domain analysis of single cell neural response to multiple stimuli presented simultaneously. The package is based on the paper by C Glynn, ST Tokdar, A Zaman, VC Caruso, JT Mohl, SM Willett, and JM Groh (2021) "Analyzing second order stochasticity of neural spiking under stimuli-bundle exposure", is in press for publication by the Annals of Applied Statistics. A preprint may be found at <arXiv:1911.04387>.
Author: Surya Tokdar <surya.tokdar@duke.edu>
Maintainer: Surya Tokdar <surya.tokdar@duke.edu>

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Package lingmatch updated to version 1.0.2 with previous version 1.0.1 dated 2021-02-25

Title: Linguistic Matching and Accommodation
Description: Measure similarity between texts. Offers a variety of processing tools and similarity metrics to facilitate flexible representation of texts and matching. Implements forms of Language Style Matching (Ireland & Pennebaker, 2010) <doi:10.1037/a0020386> and Latent Semantic Analysis (Landauer & Dumais, 1997) <doi:10.1037/0033-295X.104.2.211>.
Author: Micah Iserman
Maintainer: Micah Iserman <micah.iserman@gmail.com>

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Package gofCopula updated to version 0.4-1 with previous version 0.3-3 dated 2020-06-14

Title: Goodness-of-Fit Tests for Copulae
Description: Several Goodness-of-Fit (GoF) tests for Copulae are provided. A new hybrid test, Zhang et al. (2016) <doi:10.1016/j.jeconom.2016.02.017> is implemented which supports all of the individual tests in the package, e.g. Genest et al. (2009) <doi:10.1016/j.insmatheco.2007.10.005>. Estimation methods for the margins are provided and all the tests support parameter estimation and predefined values. The parameters are estimated by pseudo maximum likelihood but if it fails the estimation switches automatically to inversion of Kendall's tau. For reproducibility of results, the functions support the definition of seeds. Also all the tests support automatized parallelization of the bootstrapping tasks. The package provides an interface to perform new GoF tests by submitting the test statistic.
Author: Ostap Okhrin <ostap.okhrin@tu-dresden.de>, Simon Trimborn <trimborn.econometrics@gmail.com>, Martin Waltz <martin.waltz@tu-dresden.de>
Maintainer: Simon Trimborn <trimborn.econometrics@gmail.com>

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Package brglm updated to version 0.7.2 with previous version 0.7.1 dated 2020-10-12

Title: Bias Reduction in Binomial-Response Generalized Linear Models
Description: Fit generalized linear models with binomial responses using either an adjusted-score approach to bias reduction or maximum penalized likelihood where penalization is by Jeffreys invariant prior. These procedures return estimates with improved frequentist properties (bias, mean squared error) that are always finite even in cases where the maximum likelihood estimates are infinite (data separation). Fitting takes place by fitting generalized linear models on iteratively updated pseudo-data. The interface is essentially the same as 'glm'. More flexibility is provided by the fact that custom pseudo-data representations can be specified and used for model fitting. Functions are provided for the construction of confidence intervals for the reduced-bias estimates.
Author: Ioannis Kosmidis [aut, cre] (<https://orcid.org/0000-0003-1556-0302>)
Maintainer: Ioannis Kosmidis <ioannis.kosmidis@warwick.ac.uk>

Diff between brglm versions 0.7.1 dated 2020-10-12 and 0.7.2 dated 2021-04-22

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Package tsfgrnn updated to version 1.0.1 with previous version 1.0.0 dated 2021-03-08

Title: Time Series Forecasting Using GRNN
Description: A general regression neural network (GRNN) is a variant of a Radial Basis Function Network characterized by a fast single-pass learning. 'tsfgrnn' allows you to forecast time series using a GRNN model Francisco Martinez et al. (2019) <doi:10.1007/978-3-030-20521-8_17> and Weizhong Yan (2012) <doi:10.1109/TNNLS.2012.2198074>. When the forecasting horizon is higher than 1, two multi-step ahead forecasting strategies can be used. The model built is autoregressive, that is, it is only based on the observations of the time series. You can consult and plot how the prediction was done. It is also possible to assess the forecasting accuracy of the model using rolling origin evaluation.
Author: Maria Pilar Frias-Bustamante [aut], Ana Maria Martinez-Rodriguez [aut], Antonio Conde-Sanchez [aut], Francisco Martinez [aut, cre]
Maintainer: Francisco Martinez <fmartin@ujaen.es>

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Package onewaytests updated to version 2.6 with previous version 2.5 dated 2021-01-07

Title: One-Way Tests in Independent Groups Designs
Description: Performs one-way tests in independent groups designs including homoscedastic and heteroscedastic tests. These are one-way analysis of variance (ANOVA), Welch's heteroscedastic F test, Welch's heteroscedastic F test with trimmed means and Winsorized variances, Brown-Forsythe test, Alexander-Govern test, James second order test, Kruskal-Wallis test, Scott-Smith test, Box F test and Johansen F test, Generalized tests equivalent to Parametric Bootstrap and Fiducial tests. The package performs pairwise comparisons and graphical approaches. Also, the package includes Student's t test, Welch's t test and Mann-Whitney U test for two samples. Moreover, it assesses variance homogeneity and normality of data in each group via tests and plots (Dag et al., 2018, <https://journal.r-project.org/archive/2018/RJ-2018-022/RJ-2018-022.pdf>).
Author: Osman Dag [aut, cre], Anil Dolgun [aut], N. Meric Konar [aut], Sam Weerahandi [ctb], Malwane Ananda [ctb]
Maintainer: Osman Dag <osman.dag@outlook.com>

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Package xgboost updated to version 1.4.1.1 with previous version 1.3.2.1 dated 2021-01-18

Title: Extreme Gradient Boosting
Description: Extreme Gradient Boosting, which is an efficient implementation of the gradient boosting framework from Chen & Guestrin (2016) <doi:10.1145/2939672.2939785>. This package is its R interface. The package includes efficient linear model solver and tree learning algorithms. The package can automatically do parallel computation on a single machine which could be more than 10 times faster than existing gradient boosting packages. It supports various objective functions, including regression, classification and ranking. The package is made to be extensible, so that users are also allowed to define their own objectives easily.
Author: Tianqi Chen [aut], Tong He [aut, cre], Michael Benesty [aut], Vadim Khotilovich [aut], Yuan Tang [aut] (<https://orcid.org/0000-0001-5243-233X>), Hyunsu Cho [aut], Kailong Chen [aut], Rory Mitchell [aut], Ignacio Cano [aut], Tianyi Zhou [aut], Mu Li [aut], Junyuan Xie [aut], Min Lin [aut], Yifeng Geng [aut], Yutian Li [aut], XGBoost contributors [cph] (base XGBoost implementation)
Maintainer: Tong He <hetong007@gmail.com>

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Package solartime updated to version 0.0.2 with previous version 0.0.1 dated 2018-12-03

Title: Utilities Dealing with Solar Time Such as Sun Position and Time of Sunrise
Description: Provide utilities to work with solar time, i.e. where noon is exactly when sun culminates. Provides functions for computing sun position and times of sunrise and sunset.
Author: Thomas Wutzler
Maintainer: Thomas Wutzler <twutz@bgc-jena.mpg.de>

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Package projections updated to version 0.5.4 with previous version 0.5.2 dated 2020-12-17

Title: Project Future Case Incidence
Description: Provides functions and graphics for projecting daily incidence based on past incidence, and estimates of the serial interval and reproduction number. Projections are based on a branching process using a Poisson-distributed number of new cases per day, similar to the model used for estimating R in 'EpiEstim' or in 'earlyR', and described by Nouvellet et al. (2017) <doi:10.1016/j.epidem.2017.02.012>. The package provides the S3 class 'projections' which extends 'matrix', with accessors and additional helpers for handling, subsetting, merging, or adding these objects, as well as dedicated printing and plotting methods.
Author: Thibaut Jombart [aut, cre], Pierre Nouvellet [aut], Sangeeta Bhatia [ctb], Zhian N. Kamvar [ctb], Tim Taylor [ctb], Stephane Ghozzi [ctb]
Maintainer: Thibaut Jombart <thibautjombart@gmail.com>

Diff between projections versions 0.5.2 dated 2020-12-17 and 0.5.4 dated 2021-04-22

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Package MonteCarloSEM updated to version 0.0.2 with previous version 0.0.1 dated 2020-09-22

Title: Monte Carlo Data Simulation Package
Description: Monte Carlo simulation allows to test different conditions given to the correct structural equation models. This package runs Monte Carlo simulations under different conditions (such as sample size or normality of data). Within the package data sets can be simulated and run based on the given model. First, continuous and normal data sets are generated based on the given model. Later Fleishman's power method (1978) <DOI:10.1007/BF02293811> is used to add non-normality if exists. When data generation is completed (or when generated data sets are given) model test can also be run.
Author: Fatih Orcan [aut, cre] (<https://orcid.org/0000-0003-1727-0456>)
Maintainer: Fatih Orcan <fatihorcan84@gmail.com>

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Package ggplotify updated to version 0.0.6 with previous version 0.0.5 dated 2020-03-12

Title: Convert Plot to 'grob' or 'ggplot' Object
Description: Convert plot function call (using expression or formula) to 'grob' or 'ggplot' object that compatible to the 'grid' and 'ggplot2' ecosystem. With this package, we are able to e.g. using 'cowplot' to align plots produced by 'base' graphics, 'ComplexHeatmap', 'eulerr', 'grid', 'lattice', 'magick', 'pheatmap', 'vcd' etc. by converting them to 'ggplot' objects.
Author: Guangchuang Yu [aut, cre] (<https://orcid.org/0000-0002-6485-8781>)
Maintainer: Guangchuang Yu <guangchuangyu@gmail.com>

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Package exams2sakai updated to version 0.3 with previous version 0.2 dated 2021-04-09

Title: Automatic Generation of Exams in R for 'Sakai'
Description: Automatic Generation of Exams in R for 'Sakai'. Question templates in the form of the 'exams' package (see <http://www.r-exams.org/>) are transformed into XML format required by 'Sakai'.
Author: Fuensanta Arnaldos García [aut], María Victoria Caballero Pintado [aut], Úrsula Faura Martínez [aut], María Teresa Díaz Delfa [aut], Jesús María Méndez Pérez [aut, cre], Lourdes Molera Peris [aut], José Antonio Palazón Ferrando [aut], Juan José Pérez Castejón [aut], Isabel Parra Frutos [aut], Raúl Sánchez Sánchez [aut], Nicolás Andrés Ubero Pascal [aut], Nikolaus Umlauf [ctb], Achim Zeileis [ctb] (<https://orcid.org/0000-0003-0918-3766>)
Maintainer: Jesús María Méndez Pérez <jesus.mendez@ticarum.es>

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Package breathtestcore updated to version 0.8.1 with previous version 0.8.0 dated 2020-07-14

Title: Core Functions to Read and Fit 13c Time Series from Breath Tests
Description: Reads several formats of 13C data (IRIS/Wagner, BreathID) and CSV. Creates artificial sample data for testing. Fits Maes/Ghoos, Bluck-Coward self-correcting formula using 'nls', 'nlme'. Methods to fit breath test curves with Bayesian Stan methods are refactored to package 'breathteststan'. For a Shiny GUI, see package 'dmenne/breathtestshiny' on github.
Author: Dieter Menne [aut, cre], Menne Biomed Consulting Tuebingen [cph], Benjamin Misselwitz [fnd], Mark Fox [fnd], Andreas Steingoetter [dtc], University Hospital of Zurich, Dep. Gastroenterology [fnd, dtc]
Maintainer: Dieter Menne <dieter.menne@menne-biomed.de>

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 45 files changed, 1732 insertions(+), 2084 deletions(-)

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Package box updated to version 1.0.2 with previous version 1.0.1 dated 2021-03-20

Title: Write Reusable, Composable and Modular R Code
Description: A modern module system for R. Organise code into hierarchical, composable, reusable modules, and use it effortlessly across projects via a flexible, declarative dependency loading syntax.
Author: Konrad Rudolph [aut, cre] (<https://orcid.org/0000-0002-9866-7051>), Michael Schubert [ctb] (<https://orcid.org/0000-0002-6862-5221>)
Maintainer: Konrad Rudolph <konrad.rudolph@gmail.com>

Diff between box versions 1.0.1 dated 2021-03-20 and 1.0.2 dated 2021-04-22

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New package preferably with initial version 0.3.0
Package: preferably
Title: A 'pkgdown' Template
Version: 0.3.0
Authors@R: person(given = "Amir Masoud", family = "Abdol", role = c("aut", "cre"), email = "i@amirmasoudabdol.name")
Maintainer: Amir Masoud Abdol <i@amirmasoudabdol.name>
Description: This is an accessible template for 'pkgdown'. It uses two bootstrap themes, Flatly and Darkly and utilizes the 'prefers-color-scheme' CSS variable to automatically serve either of the two based on user’s operating system setting, or allowing them to manually toggle between them.
License: MIT + file LICENSE
URL: https://preferably.amirmasoudabdol.name
BugReports: https://github.com/amirmasoudabdol/preferably/issues
Depends: R (>= 3.4.0)
Imports: pkgdown, knitr, rmarkdown
VignetteBuilder: knitr
Encoding: UTF-8
Language: en-US
NeedsCompilation: no
Packaged: 2021-04-19 07:49:37 UTC; amabdol
Author: Amir Masoud Abdol [aut, cre]
Repository: CRAN
Date/Publication: 2021-04-22 07:20:02 UTC

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New package penalizedclr with initial version 0.1.0
Package: penalizedclr
Title: Integrative Penalized Conditional Logistic Regression
Version: 0.1.0
Authors@R: c( person(given = "Vera", family = "Djordjilovi\'c", role = c("aut", "cre"), email = "vera.djordjilovic@unive.it", comment = c(ORCID = "https://orcid.org/0000-0002-7670-3111")), person(given = "Erica", family = "Ponzi", role = c("aut"), email = "erica.ponzi@medisin.uio.no"))
Description: Implements L1 and L2 penalized conditional logistic regression with penalty factors allowing for integration of multiple data sources. Implements stability selection for variable selection.
License: MIT + file LICENSE
Encoding: UTF-8
Imports: penalized, survival, clogitL1, stats, tidyverse
Suggests: parallel, knitr, rmarkdown
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2021-04-21 17:08:54 UTC; veradj
Author: Vera Djordjilovi'c [aut, cre] (<https://orcid.org/0000-0002-7670-3111>), Erica Ponzi [aut]
Maintainer: Vera Djordjilovi'c <vera.djordjilovic@unive.it>
Repository: CRAN
Date/Publication: 2021-04-22 07:30:02 UTC

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New package paleopop with initial version 2.1.0
Package: paleopop
Title: Pattern-Oriented Modeling Framework for Coupled Niche-Population Paleo-Climatic Models
Version: 2.1.0
Authors@R: c( person("Sean", "Haythorne", email = "sean.haythorne@adelaide.edu.au", role = c("aut")), person("Julia", "Pilowsky", email = "julia.pilowsky@adelaide.edu.au", role = c("aut", "cre"), comment = c(ORCID = "https://orcid.org/0000-0002-6376-2585")))
Maintainer: Julia Pilowsky <julia.pilowsky@adelaide.edu.au>
URL: https://github.com/GlobalEcologyLab/paleopop/
BugReports: https://github.com/GlobalEcologyLab/paleopop/issues
Description: This extension of the poems pattern-oriented modeling (POM) framework provides a collection of modules and functions customized for paleontological time-scales, and optimized for single-generation transitions and large populations, across multiple generations.
Depends: R (>= 3.6.0)
License: GPL (>= 3)
Encoding: UTF-8
LazyData: true
Imports: poems (>= 1.0.0), R6 (>= 2.5.0), sf (>= 0.9)
Collate: data.R PaleoPopModel.R PaleoPopResults.R PaleoRegion.R paleopop_simulator.R paleopop.R region_subset.R
Suggests: testthat (>= 3.0.0), knitr, rmarkdown, markdown, dplyr, raster
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2021-04-22 01:40:27 UTC; Julia Pilowsky
Author: Sean Haythorne [aut], Julia Pilowsky [aut, cre] (<https://orcid.org/0000-0002-6376-2585>)
Repository: CRAN
Date/Publication: 2021-04-22 07:30:06 UTC

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New package maclogp with initial version 0.1.1
Package: maclogp
Title: Measures of Uncertainty for Model Selection
Version: 0.1.1
Authors@R: c(person("Yuanyuan", "Li", role = c("aut", "cre"), email = "yynli9696@gmail.com"), person("Jiming", "Jiang", role = "ths"))
Maintainer: Yuanyuan Li <yynli9696@gmail.com>
Description: Following the common types of measures of uncertainty for parameter estimation, two measures of uncertainty were proposed for model selection, see Liu, Li and Jiang (2020) <doi:10.1007/s11749-020-00737-9>. The first measure is a kind of model confidence set that relates to the variation of model selection, called Mac. The second measure focuses on error of model selection, called LogP. They are all computed via bootstrapping. This package provides functions to compute these two measures. Furthermore, a similar model confidence set adapted from Bayesian Model Averaging can also be computed using this package.
License: GPL (>= 3)
URL: https://github.com/YuanyuanLi96/maclogp
BugReports: https://github.com/YuanyuanLi96/maclogp/issues
Encoding: UTF-8
LazyData: true
Imports: BMA, plot.matrix, rlist, utils
NeedsCompilation: no
Packaged: 2021-04-22 04:50:15 UTC; yuanyuanli
Depends: R (>= 3.5.0)
Author: Yuanyuan Li [aut, cre], Jiming Jiang [ths]
Repository: CRAN
Date/Publication: 2021-04-22 07:40:02 UTC

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New package iriR with initial version 0.2.2
Package: iriR
Title: Global Innovation Through Company Level Data
Version: 0.2.2
Authors@R: person(given = "Thierry", family = "Warin", role = c("aut", "cre"), email = "thierry.warin@hec.ca", comment = c(ORCID = "0000-0002-5921-3428"))
Description: Researchers and analysts have access to more than 7,500 innovative companies worldwide, which are or have been part of the top 1,000 innovative companies. They can access the six parameters that compose the global IRI Scoreboard's data on R&D: Country, Year, Company's name, Industry, Indicator and Company's rank. Please cite: Warin, Th. (2020) "iiriR: An R Package for the EU Industrial R&D Investment Scoreboard", <doi:10.6084/m9.figshare.11774640.v5>.
URL: https://github.com/warint/iriR/
Imports: gsheet, dplyr, reshape2, ggplot2, ggsci, WDI, scales, stats
License: MIT + file LICENSE
Encoding: UTF-8
VignetteBuilder: knitr
Suggests: rmarkdown, knitr
NeedsCompilation: no
Packaged: 2021-04-21 16:20:43 UTC; thierryw
Author: Thierry Warin [aut, cre] (<https://orcid.org/0000-0002-5921-3428>)
Maintainer: Thierry Warin <thierry.warin@hec.ca>
Repository: CRAN
Date/Publication: 2021-04-22 07:20:05 UTC

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Package genieclust updated to version 1.0.0 with previous version 0.9.8 dated 2021-01-08

Title: The Genie++ Hierarchical Clustering Algorithm with Noise Points Detection
Description: A retake on the Genie algorithm - a robust hierarchical clustering method (Gagolewski, Bartoszuk, Cena, 2016 <DOI:10.1016/j.ins.2016.05.003>). Now faster and more memory efficient; determining the whole hierarchy for datasets of 10M points in low dimensional Euclidean spaces or 100K points in high-dimensional ones takes only 1-2 minutes. Allows clustering with respect to mutual reachability distances so that it can act as a noise point detector or a robustified version of 'HDBSCAN*' (that is able to detect a predefined number of clusters and hence it does not dependent on the somewhat fragile 'eps' parameter). The package also features an implementation of economic inequity indices (the Gini, Bonferroni index) and external cluster validity measures (partition similarity scores; e.g., the adjusted Rand, Fowlkes-Mallows, adjusted mutual information, pair sets index). See also the 'Python' version of 'genieclust' available on 'PyPI', which supports sparse data, more metrics, and even larger datasets.
Author: Marek Gagolewski [aut, cre, cph] (<https://orcid.org/0000-0003-0637-6028>), Maciej Bartoszuk [ctb], Anna Cena [ctb], Peter M. Larsen [ctb]
Maintainer: Marek Gagolewski <marek@gagolewski.com>

Diff between genieclust versions 0.9.8 dated 2021-01-08 and 1.0.0 dated 2021-04-22

 DESCRIPTION                  |   12 +++----
 MD5                          |   51 ++++++++++++++++---------------
 NEWS                         |   41 +++++++++----------------
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 src/r_compare_partitions.cpp |   14 ++++----
 src/r_emst.cpp               |   69 ++++++++++++++++++++++---------------------
 src/r_inequity.cpp           |    4 --
 27 files changed, 147 insertions(+), 157 deletions(-)

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New package exploratory with initial version 0.3.13
Package: exploratory
Title: A Tool for Large-Scale Exploratory Analyses
Version: 0.3.13
Authors@R: person(given = "Jin", family = "Kim", role = c("aut", "cre"), email = "jin.m.kim@yale.edu", comment = c(ORCID = "https://orcid.org/0000-0002-5013-3958"))
Description: Conduct numerous exploratory analyses in an instant with a point-and-click interface. With one simple command, this tool launches a Shiny App on the local machine. Drag and drop variables in a data set to categorize them as possible independent, dependent, moderating, or mediating variables. Then run dozens (or hundreds) of analyses instantly to uncover any statistically significant relationships among variables. Any relationship thus uncovered should be tested in follow-up studies. This tool is designed only to facilitate exploratory analyses and should NEVER be used for p-hacking. Many of the functions used in this package are direct copies of functions in the R Package 'kim' and 'ezr'. Selected References: Chang et al. (2021) <https://CRAN.R-project.org/package=shiny>. Chang et al. (2018) <https://CRAN.R-project.org/package=shinydashboard>. Cohen (1988) <doi:10.4324/9780203771587>. Dowle et al. (2021) <https://CRAN.R-project.org/package=data.table>. Ioannidis (2005) <doi:10.1371/journal.pmed.0020124> Kim (2021) <doi:10.5281/zenodo.4619237>. Kim (2020) <https://CRAN.R-project.org/package=ezr>. Simmons et al. (2011) <doi:10.1177/0956797611417632> Tingley et al. (2019) <https://CRAN.R-project.org/package=mediation>. Wickham et al. (2020) <https://CRAN.R-project.org/package=ggplot2>.
License: GPL-3
URL: https://exploratoryonly.com
BugReports: https://github.com/jinkim3/exploratory/issues
Imports: data.table, DT, ggplot2, ggridges, lemon, lm.beta, mediation, remotes, shiny, shinydashboard, weights
Suggests: moments
Encoding: UTF-8
NeedsCompilation: no
Packaged: 2021-04-21 09:43:27 UTC; c
Author: Jin Kim [aut, cre] (<https://orcid.org/0000-0002-5013-3958>)
Maintainer: Jin Kim <jin.m.kim@yale.edu>
Repository: CRAN
Date/Publication: 2021-04-22 07:10:02 UTC

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New package epanet2toolkit with initial version 0.5.1
Package: epanet2toolkit
Title: Call 'EPANET' Functions to Simulate Pipe Networks
Version: 0.5.1
Date: 2021-04-21
Authors@R: c( person("Ernesto", "Arandia", email="earandia.ie@gmail.com", role='aut'), person("Bradley", "Eck", email="brad@bradeck.net", role = c('aut','cre')), person("Lew", "Rossman", role='aut'), person("Michael Tryby", role = 'ctb'), person("Sam","Hatchett", role = 'ctb'), person("Feng","Shang", role = 'ctb'), person("James","Uber", role = 'ctb'), person("Tom","Taxon", role = 'ctb'), person("Hyoungmin","Woo", role = 'ctb'), person("Jinduan","Chen", role = 'ctb'), person("Yunier","Soad", role = 'ctb'), person("Mike","Kane", role = 'ctb'), person("Demetrios","Eliades", role = 'ctb'), person("Will","Furnass", role = 'ctb'), person("Steffen","Macke", role = 'ctb'), person("Marios", "Kyriakou", role = 'ctb'), person("Elad","Salomons", role = 'ctb'), person("Maurizio","Cingi", role = 'ctb'), person("Bryant","McDonnell", role = 'ctb'), person("Angela","Marchi",role='ctb'), person("Markus","Sunela",role='ctb'), person("Milad","Ghiami",role='ctb'), person("IBM Corp.", role = 'cph'), person("Open Water Analytics", role = 'cph') )
Maintainer: Bradley Eck <brad@bradeck.net>
Suggests: testthat, epanetReader
Description: Enables simulation of water piping networks using 'EPANET'. The package provides functions from the 'EPANET' programmer's toolkit as R functions so that basic or customized simulations can be carried out from R. The package uses 'EPANET' version 2.2 from Open Water Analytics <https://github.com/OpenWaterAnalytics/EPANET/releases/tag/v2.2>.
License: MIT + file LICENSE
Copyright: COPYRIGHTS
URL: https://github.com/bradleyjeck/epanet2toolkit
NeedsCompilation: yes
Packaged: 2021-04-21 20:52:49 UTC; brad
Author: Ernesto Arandia [aut], Bradley Eck [aut, cre], Lew Rossman [aut], Michael Tryby [ctb], Sam Hatchett [ctb], Feng Shang [ctb], James Uber [ctb], Tom Taxon [ctb], Hyoungmin Woo [ctb], Jinduan Chen [ctb], Yunier Soad [ctb], Mike Kane [ctb], Demetrios Eliades [ctb], Will Furnass [ctb], Steffen Macke [ctb], Marios Kyriakou [ctb], Elad Salomons [ctb], Maurizio Cingi [ctb], Bryant McDonnell [ctb], Angela Marchi [ctb], Markus Sunela [ctb], Milad Ghiami [ctb], IBM Corp. [cph], Open Water Analytics [cph]
Repository: CRAN
Date/Publication: 2021-04-22 07:10:05 UTC

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New package dsims with initial version 0.1.1
Package: dsims
Depends: dssd (>= 0.2.2)
Imports: mrds, Distance, sf, sp, ggplot2, mgcv, rgeos, methods, rstudioapi, gridExtra, rlang
Suggests: testthat, parallel, pbapply, knitr, lwgeom, rmarkdown
VignetteBuilder: knitr
Title: Distance Sampling Simulations
Version: 0.1.1
Author: Laura Marshall <lhm@st-and.ac.uk>
Maintainer: Laura Marshall <lhm@st-and.ac.uk>
Description: Performs distance sampling simulations. 'dsims' repeatedly generates instances of a user defined population within a given survey region. It then generates realisations of a survey design and simulates the detection process. The data are then analysed so that the results can be compared for accuracy and precision across all replications. This process allows users to optimise survey designs for their specific set of survey conditions. The effects of uncertainty in population distribution or parameters can be investigated under a number of simulations so that users can be confident that they have achieved a robust survey design before deploying vessels into the field. The distance sampling designs used in this package from 'dssd' are detailed in Chapter 7 of Advanced Distance Sampling, Buckland et. al. (2008, ISBN-13: 978-0199225873). General distance sampling methods are detailed in Introduction to Distance Sampling: Estimating Abundance of Biological Populations, Buckland et. al. (2004, ISBN-13: 978-0198509271). Find out more about estimating animal/plant abundance with distance sampling at <http://distancesampling.org/>.
License: GPL (>= 2)
Language: en-GB
URL: https://github.com/DistanceDevelopment/dsims
BugReports: https://github.com/DistanceDevelopment/dsims/issues
Encoding: UTF-8
Collate: 'AICc.R' 'generic.functions.R' 'Density.Summary.R' 'Density.R' 'Population.Description.R' 'Detectability.R' 'Population.R' 'Survey.R' 'DS.Analysis.R' 'Simulation.R' 'ClassConstructors.R' 'Simulation.Summary.R' 'Survey.LT.R' 'Survey.PT.R' 'accumulate.PP.results.R' 'accumulate.warnings.R' 'add.covariate.values.R' 'add.summary.results.R' 'calc.perp.dists.R' 'calc.rad.dists.R' 'calculate.scale.param.R' 'check.covariates.R' 'check.transects.R' 'create.results.arrays.R' 'description.summary.R' 'dsims-package.R' 'generate.pop.D.R' 'generate.pop.N.R' 'get.density.surface.R' 'message.handler.R' 'modify.strata.for.analysis.R' 'rtpois.R' 'run.simulation.R' 'simulate.detections.R' 'single.sim.loop.R' 'store.ddf.results.R' 'store.dht.results.R'
NeedsCompilation: no
Packaged: 2021-04-21 10:05:22 UTC; lhm
Repository: CRAN
Date/Publication: 2021-04-22 07:20:11 UTC

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New package dimensio with initial version 0.2.0
Package: dimensio
Title: Multivariate Data Analysis
Version: 0.2.0
Authors@R: c(person(given = "Nicolas", family = "Frerebeau", role = c("aut", "cre"), email = "nicolas.frerebeau@u-bordeaux-montaigne.fr", comment = c(ORCID = "0000-0001-5759-4944")), person(given = "Jean-Baptiste", family = "Fourvel", role = "ctb", email = "fourvel@mmsh.univ-aix.fr", comment = c(ORCID = "0000-0002-1061-4642")), person(given = "Brice", family = "Lebrun", role = "ctb", email = "brice.lebrun@u-bordeaux-montaigne.fr", comment = c(ORCID = "0000-0001-7503-8685")))
Maintainer: Nicolas Frerebeau <nicolas.frerebeau@u-bordeaux-montaigne.fr>
Description: Simple Principal Components Analysis (PCA) and Correspondence Analysis (CA) based on the Singular Value Decomposition (SVD). This package provides S4 classes and methods to compute, extract, summarize and visualize results of multivariate data analysis. It also includes methods for partial bootstrap validation described in Greenacre (1984) <isbn: 978-0-12-299050-2> and Lebart et al. (2006) <isbn: 978-2-10-049616-7>.
License: GPL (>= 3)
URL: https://dimensio.tesselle.org, https://github.com/tesselle/dimensio
BugReports: https://github.com/tesselle/dimensio/issues
Depends: R (>= 3.3)
Imports: ggplot2, methods, rlang
Suggests: folio, FactoMineR, ggrepel, khroma, testthat (>= 3.0.0), vdiffr
Encoding: UTF-8
Collate: 'AllClasses.R' 'AllGenerics.R' 'bootstrap.R' 'ca.R' 'dimensio-package.R' 'helpers.R' 'joint.R' 'mutators.R' 'pca.R' 'plot.R' 'show.R' 'subset.R' 'summary.R' 'zzz.R'
NeedsCompilation: no
Packaged: 2021-04-21 09:39:06 UTC; nicolas
Author: Nicolas Frerebeau [aut, cre] (<https://orcid.org/0000-0001-5759-4944>), Jean-Baptiste Fourvel [ctb] (<https://orcid.org/0000-0002-1061-4642>), Brice Lebrun [ctb] (<https://orcid.org/0000-0001-7503-8685>)
Repository: CRAN
Date/Publication: 2021-04-22 07:10:09 UTC

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New package critpath with initial version 0.1.2
Package: critpath
Title: Setting the Critical Path
Version: 0.1.2
Author: Adam Kucharski
Maintainer: Adam Kucharski <aqcharski@interia.pl>
Description: Solving the problem of project management using CPM (Critical Path Method), PERT (Program Evaluation and Review Technique) and LESS (Least Cost Estimating and Scheduling) methods. The package sets the critical path, schedule and Gantt chart. In addition, it allows you to draw a graph with marked critical activities. For more information about project management, see: Taha H. A. (2017, ISBN:978-1-292-16554-7), Konarzewska I., Jewczak M., Kucharski A. (2020, ISBN:978-83-8220-112-3), Rama Murthy P. (2007, ISBN:978-81-224-2944-2).
License: GPL-2
Encoding: UTF-8
LazyData: true
Imports: DiagrammeR, ggplot2, reshape2
Suggests: knitr, rmarkdown
VignetteBuilder: knitr
Depends: R (>= 4.0.0)
Date: 2021-04-21
NeedsCompilation: no
Packaged: 2021-04-22 05:43:52 UTC; adamk
Repository: CRAN
Date/Publication: 2021-04-22 07:50:02 UTC

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New package biokNN with initial version 0.1.0
Package: biokNN
Title: Bi-Objective k-Nearest Neighbors Imputation for Multilevel Data
Version: 0.1.0
Depends: R (>= 2.10)
Authors@R: c(person("Maximiliano Cubillos", role = c("aut", "cre"), email = "mcub@econ.au.dk", comment = c(ORCID = "0000-0002-2826-9728")))
Maintainer: Maximiliano Cubillos <mcub@econ.au.dk>
Description: The bi-objective k-nearest neighbors method (biokNN) is an imputation method designed to estimate missing values on data with a multilevel structure. The original algorithm is an extension of the k-nearest neighbors method proposed by Bertsimas et al. (2017) (<https://jmlr.org/papers/v18/17-073.html>) using a bi-objective approach. A brief description of the method can be found in Cubillos (2021) (<https://pure.au.dk/portal/files/214627979/biokNN.pdf>). The 'biokNN' package provides an R implementation of the method for datasets with continuous variables (e.g. employee productivity, student grades) and a categorical class variable (e.g. department, school). Given an incomplete dataset with such structure, this package produces complete datasets using both single and multiple imputation, including visualization tools to better understand the pattern of the missing values.
License: GPL (>= 2)
URL: https://github.com/mcubillos3/biokNN
BugReports: https://github.com/mcubillos3/biokNN/issues
Suggests: knitr, rmarkdown, testthat
Encoding: UTF-8
LazyData: true
Imports: dplyr, cluster, mice, stats, magrittr, ggplot2, tidyr, desc, lme4, mitml
NeedsCompilation: no
Packaged: 2021-04-14 14:10:46 UTC; au629204
Author: Maximiliano Cubillos [aut, cre] (<https://orcid.org/0000-0002-2826-9728>)
Repository: CRAN
Date/Publication: 2021-04-22 07:20:15 UTC

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Package sparta updated to version 0.7.3 with previous version 0.7.2 dated 2021-04-03

Title: Sparse Tables
Description: Fast Multiplication and Marginalization of Sparse Tables.
Author: Mads Lindskou [aut, cre]
Maintainer: Mads Lindskou <mads@math.aau.dk>

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Package runner updated to version 0.4.0 with previous version 0.3.8 dated 2021-02-22

Title: Running Operations for Vectors
Description: Lightweight library for rolling windows operations. Package enables full control over the window length, window lag and a time indices. With a runner one can apply any R function on a rolling windows. The package eases work with equally and unequally spaced time series.
Author: Dawid Kałędkowski [aut, cre] (<https://orcid.org/0000-0001-9533-457X>)
Maintainer: Dawid Kałędkowski <dawid.kaledkowski@gmail.com>

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

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

2020-09-25 2.0.3
2020-07-19 2.0.2
2020-03-02 2.0.1
2020-02-17 2.0.0
2019-09-10 1.10.1
2019-07-11 1.10.0
2019-04-25 1.9.2
2019-04-17 1.9.1
2019-02-04 1.9
2018-01-23 1.8
2017-07-15 1.7
2017-06-08 1.6
2017-03-03 1.5
2016-02-02 1.4
2015-10-14 1.3
2015-05-11 1.2
2015-03-06 1.1

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Package plethem (with last version 1.1.0) was removed from CRAN

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

2020-11-04 1.1.0

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Package SeqNet (with last version 1.1.0) was removed from CRAN

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

2019-12-18 1.1.0
2019-06-24 1.0.0

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Package DUBStepR updated to version 1.1.1 with previous version 1.1 dated 2021-03-15

Title: Correlation-Based Feature Selection for Single-Cell RNA Sequencing Data
Description: Determining the optimal set of feature genes to characterise cell types in single-cell RNA sequencing data using stepwise regression on gene-gene correlations. <doi:10.1101/2020.10.07.330563>.
Author: Bobby Ranjan [aut, cre], Kunal Mishra [ctb], Shyam Lab [cph], Bryan Hanson [ctb], Damian Coventry [ctb], Brandon Crosby [ctb], Gregoire Thomas [ctb]
Maintainer: Bobby Ranjan <ranjan_bobby@gis.a-star.edu.sg>

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Package BeSS updated to version 2.0.3 with previous version 2.0.2 dated 2021-01-23

Title: Best Subset Selection in Linear, Logistic and CoxPH Models
Description: An implementation of best subset selection in generalized linear model and Cox proportional hazard model via the primal dual active set algorithm proposed by Wen, C., Zhang, A., Quan, S. and Wang, X. (2020) <doi:10.18637/jss.v094.i04>. The algorithm formulates coefficient parameters and residuals as primal and dual variables and utilizes efficient active set selection strategies based on the complementarity of the primal and dual variables.
Author: Canhong Wen [aut, cre], Aijun Zhang [aut], Shijie Quan [aut], Xueqin Wang [aut]
Maintainer: Canhong Wen <wencanhong@gmail.com>

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Package wru updated to version 0.1-11 with previous version 0.1-10 dated 2020-10-22

Title: Who are You? Bayesian Prediction of Racial Category Using Surname and Geolocation
Description: Predicts individual race/ethnicity using surname, geolocation, and other attributes, such as gender and age. The method utilizes the Bayes' Rule to compute the posterior probability of each racial category for any given individual. The package implements methods described in Imai and Khanna (2015) "Improving Ecological Inference by Predicting Individual Ethnicity from Voter Registration Records" <DOI:10.1093/pan/mpw001>.
Author: Kabir Khanna [aut, cre], Kosuke Imai [aut]
Maintainer: Kabir Khanna <kabirkhanna@gmail.com>

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Package tzdb updated to version 0.1.1 with previous version 0.1.0 dated 2021-03-04

Title: Time Zone Database Information
Description: Provides an up-to-date copy of the Internet Assigned Numbers Authority (IANA) Time Zone Database. It is updated periodically to reflect changes made by political bodies to time zone boundaries, UTC offsets, and daylight saving time rules. Additionally, this package provides a C++ interface for working with the 'date' library. 'date' provides comprehensive support for working with dates and date-times, which this package exposes to make it easier for other R packages to utilize. Headers are provided for calendar specific calculations, along with a limited interface for time zone manipulations.
Author: Davis Vaughan [aut, cre], Howard Hinnant [cph] (Author of the included date library), RStudio [cph, fnd]
Maintainer: Davis Vaughan <davis@rstudio.com>

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Package rsolr updated to version 0.0.11 with previous version 0.0.10 dated 2020-10-12

Title: R to Solr Interface
Description: A comprehensive R API for querying Apache Solr databases. A Solr core is represented as a data frame or list that supports Solr-side filtering, sorting, transformation and aggregation, all through the familiar base R API. Queries are processed lazily, i.e., a query is only sent to the database when the data are required.
Author: Michael Lawrence, Gabe Becker, Jan Vogel
Maintainer: Michael Lawrence <michafla@gene.com>

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Package POFIBGE updated to version 0.1.1 with previous version 0.1.0 dated 2020-12-16

Title: Downloading, Reading and Analysing POF Microdata
Description: Provides tools for downloading, reading and analysing the POF, a household survey from Brazilian Institute of Geography and Statistics - IBGE. The data must be downloaded from the official website <https://www.ibge.gov.br/>. Further analysis must be made using package 'survey'.
Author: Gabriel Assuncao [aut, cre], Luna Hidalgo [aut], Douglas Braga [ctb]
Maintainer: Gabriel Assuncao <pacotesipd@ibge.gov.br>

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Package PNADcIBGE updated to version 0.6.3 with previous version 0.6.2 dated 2021-01-26

Title: Downloading, Reading and Analysing PNADC Microdata
Description: Provides tools for downloading, reading and analysing the PNADC, a household survey from Brazilian Institute of Geography and Statistics - IBGE. The data must be downloaded from the official website <https://www.ibge.gov.br/>. Further analysis must be made using package 'survey'.
Author: Douglas Braga [aut], Gabriel Assuncao [aut, cre], Luna Hidalgo [ctb]
Maintainer: Gabriel Assuncao <pacotesipd@ibge.gov.br>

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Package pcalg updated to version 2.7-2 with previous version 2.7-1 dated 2021-01-09

Title: Methods for Graphical Models and Causal Inference
Description: Functions for causal structure learning and causal inference using graphical models. The main algorithms for causal structure learning are PC (for observational data without hidden variables), FCI and RFCI (for observational data with hidden variables), and GIES (for a mix of data from observational studies (i.e. observational data) and data from experiments involving interventions (i.e. interventional data) without hidden variables). For causal inference the IDA algorithm, the Generalized Backdoor Criterion (GBC), the Generalized Adjustment Criterion (GAC) and some related functions are implemented. Functions for incorporating background knowledge are provided.
Author: Markus Kalisch [aut, cre], Alain Hauser [aut], Martin Maechler [aut], Diego Colombo [ctb], Doris Entner [ctb], Patrik Hoyer [ctb], Antti Hyttinen [ctb], Jonas Peters [ctb], Nicoletta Andri [ctb], Emilija Perkovic [ctb], Preetam Nandy [ctb], Philipp Ruetimann [ctb], Daniel Stekhoven [ctb], Manuel Schuerch [ctb], Marco Eigenmann [ctb], Leonard Henckel [ctb], Joris Mooij [ctb]
Maintainer: Markus Kalisch <kalisch@stat.math.ethz.ch>

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Package Eagle updated to version 2.4.4 with previous version 2.4.3 dated 2021-01-12

Title: Multiple Locus Association Mapping on a Genome-Wide Scale
Description: An implementation of multiple-locus association mapping on a genome-wide scale. 'Eagle' can handle inbred and outbred study populations, populations of arbitrary unknown complexity, and data larger than the memory capacity of the computer. Since 'Eagle' is based on linear mixed models, it is best suited to the analysis of data on continuous traits. However, it can tolerate non-normal data. 'Eagle' reports, as its findings, the best set of snp in strongest association with a trait. For users unfamiliar with R, to perform an analysis, run 'OpenGUI()'. This opens a web browser to the menu-driven user interface for the input of data, and for performing genome-wide analysis.
Author: Andrew George [aut, cre], Joshua Bowden [ctb], Ryan Stephenson [ctb], Hyun Kang [ctb], Noah Zaitlen [ctb], Claire Wade [ctb], Andrew Kirby [ctb], David Heckerman [ctb], Mark Daly [ctb], Eleazar Eskin [ctb]
Maintainer: Andrew George <andrew.george@csiro.au>

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Package drat updated to version 0.2.0 with previous version 0.1.8 dated 2020-07-18

Title: 'Drat' R Archive Template
Description: Creation and use of R Repositories via helper functions to insert packages into a repository, and to add repository information to the current R session. Two primary types of repositories are support: gh-pages at GitHub, as well as local repositories on either the same machine or a local network. Drat is a recursive acronym: Drat R Archive Template.
Author: Dirk Eddelbuettel with contributions by Carl Boettiger, Neal Fultz, Sebastian Gibb, Colin Gillespie, Jan Górecki, Matt Jones, Thomas Leeper, Steven Pav, Jan Schulz, Christoph Stepper, Felix G.M. Ernst and Patrick Schratz.
Maintainer: Dirk Eddelbuettel <edd@debian.org>

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 34 files changed, 961 insertions(+), 1754 deletions(-)

More information about drat at CRAN
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Package dbscan updated to version 1.1-7 with previous version 1.1-6 dated 2021-02-26

Title: Density Based Clustering of Applications with Noise (DBSCAN) and Related Algorithms
Description: A fast reimplementation of several density-based algorithms of the DBSCAN family for spatial data. Includes the clustering algorithms DBSCAN (density-based spatial clustering of applications with noise) and HDBSCAN (hierarchical DBSCAN), the ordering algorithm OPTICS (ordering points to identify the clustering structure), and the outlier detection algorithm LOF (local outlier factor). The implementations use the kd-tree data structure (from library ANN) for faster k-nearest neighbor search. An R interface to fast kNN and fixed-radius NN search is also provided. Hahsler, Piekenbrock and Doran (2019) <doi:10.18637/jss.v091.i01>.
Author: Michael Hahsler [aut, cre, cph], Matthew Piekenbrock [aut, cph], Sunil Arya [ctb, cph], David Mount [ctb, cph]
Maintainer: Michael Hahsler <mhahsler@lyle.smu.edu>

Diff between dbscan versions 1.1-6 dated 2021-02-26 and 1.1-7 dated 2021-04-22

 DESCRIPTION               |   10 +-
 MD5                       |   63 ++++++++--------
 NEWS.md                   |    9 ++
 R/LOF.R                   |   88 +++++++++++++++++++----
 R/RcppExports.R           |    4 +
 R/dbscan.R                |    9 --
 R/frNN.R                  |    8 --
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 R/optics.R                |   10 +-
 R/pointdensity.R          |    7 -
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 src/R_dbscan.cpp          |    2 
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 src/R_regionQuery.h       |    2 
 src/RcppExports.cpp       |   17 ++++
 tests/testthat/test-lof.R |  174 ++++++++++++++++++++++++++++++++++++++++++++--
 vignettes/dbscan.Rnw      |   19 ++---
 33 files changed, 501 insertions(+), 248 deletions(-)

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Package COVIDIBGE updated to version 0.1.3 with previous version 0.1.2 dated 2021-01-31

Title: Downloading, Reading and Analysing PNAD COVID19 Microdata
Description: Provides tools for downloading, reading and analysing the PNAD COVID19, a household survey from Brazilian Institute of Geography and Statistics - IBGE. The data must be downloaded from the official website <https://www.ibge.gov.br/>. Further analysis must be made using package 'survey'.
Author: Gabriel Assuncao [aut, cre], Luna Hidalgo [aut], Douglas Braga [ctb]
Maintainer: Gabriel Assuncao <pacotesipd@ibge.gov.br>

Diff between COVIDIBGE versions 0.1.2 dated 2021-01-31 and 0.1.3 dated 2021-04-22

 DESCRIPTION          |   11 +++++------
 MD5                  |   22 +++++++++++-----------
 NAMESPACE            |    2 ++
 R/covid_deflator.R   |    6 +++---
 R/covid_design.R     |   10 +++++-----
 R/covid_labeller.R   |    4 ++--
 R/example.R          |    4 ++--
 R/get_covid.R        |   45 +++++++++++++++++++++++++--------------------
 R/read_covid.R       |    4 ++--
 man/covid_design.Rd  |    4 ++--
 man/covid_example.Rd |    2 +-
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 12 files changed, 63 insertions(+), 57 deletions(-)

More information about COVIDIBGE at CRAN
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