Sun, 31 May 2020

Package tidyjson updated to version 0.3.1 with previous version 0.3.0 dated 2020-05-28

Title: Tidy Complex 'JSON'
Description: Turn complex 'JSON' data into tidy data frames.
Author: Jeremy Stanley [aut], Cole Arendt [aut, cre]
Maintainer: Cole Arendt <cole@rstudio.com>

Diff between tidyjson versions 0.3.0 dated 2020-05-28 and 0.3.1 dated 2020-05-31

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More information about tidyjson at CRAN
Permanent link

Package sundialr updated to version 0.1.4 with previous version 0.1.3 dated 2019-06-09

Title: An Interface to 'SUNDIALS' Ordinary Differential Equation (ODE) Solvers
Description: Provides a way to call the functions in 'SUNDIALS' C ODE solving library (<https://computation.llnl.gov/projects/sundials>). Currently the serial version of ODE solver, 'CVODE', sensitivity calculator 'CVODES' and differential algebraic solver 'IDA' from the 'SUNDIALS' library are implemented. The package requires ODE to be written as an 'R' or 'Rcpp' function and does not require the 'SUNDIALS' library to be installed on the local machine.
Author: Satyaprakash Nayak [aut, cre, cph] (<https://orcid.org/0000-0001-7225-1317>), Lawrence Livermore National Security [cph], Southern Methodist University [cph]
Maintainer: Satyaprakash Nayak <sn248@cornell.edu>

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More information about sundialr at CRAN
Permanent link

Package robotstxt updated to version 0.7.4 with previous version 0.6.2 dated 2018-07-18

Title: A 'robots.txt' Parser and 'Webbot'/'Spider'/'Crawler' Permissions Checker
Description: Provides functions to download and parse 'robots.txt' files. Ultimately the package makes it easy to check if bots (spiders, crawler, scrapers, ...) are allowed to access specific resources on a domain.
Author: Peter Meissner [aut, cre], Kun Ren [aut, cph] (Author and copyright holder of list_merge.R.), Oliver Keys [ctb] (original release code review), Rich Fitz John [ctb] (original release code review)
Maintainer: Peter Meissner <retep.meissner@gmail.com>

Diff between robotstxt versions 0.6.2 dated 2018-07-18 and 0.7.4 dated 2020-05-31

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Package MCMCpack updated to version 1.4-8 with previous version 1.4-7 dated 2020-05-08

Title: Markov Chain Monte Carlo (MCMC) Package
Description: Contains functions to perform Bayesian inference using posterior simulation for a number of statistical models. Most simulation is done in compiled C++ written in the Scythe Statistical Library Version 1.0.3. All models return 'coda' mcmc objects that can then be summarized using the 'coda' package. Some useful utility functions such as density functions, pseudo-random number generators for statistical distributions, a general purpose Metropolis sampling algorithm, and tools for visualization are provided.
Author: Andrew D. Martin [aut], Kevin M. Quinn [aut], Jong Hee Park [aut,cre], Ghislain Vieilledent [ctb], Michael Malecki[ctb], Matthew Blackwell [ctb], Keith Poole [ctb], Craig Reed [ctb], Ben Goodrich [ctb], Ross Ihaka [cph], The R Development Core Team [cph], The R Foundation [cph], Pierre L'Ecuyer [cph], Makoto Matsumoto [cph], Takuji Nishimura [cph]
Maintainer: Jong Hee Park <jongheepark@snu.ac.kr>

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Package GNAR updated to version 1.1.0 with previous version 1.0 dated 2019-10-29

Title: Methods for Fitting Network Time Series Models
Description: Simulation of, and fitting models for, Generalised Network Autoregressive (GNAR) time series models which take account of network structure. Such models are described in Knight et al. (2016), see <arXiv:1603.03221>.
Author: Kathryn Leeming [aut], Guy Nason [aut], Matt Nunes [aut, cre], Marina Knight [ctb]
Maintainer: Matt Nunes <nunesrpackages@gmail.com>

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Package EMSS updated to version 1.0.1 with previous version 1.0.0 dated 2020-05-29

Title: Some EM-Type Estimation Methods for the Heckman Selection Model
Description: Some EM-type algorithms to estimate parameters for the well-known Heckman selection model are provided in the package. Such algorithms are as follow: ECM(Expectation/Conditional Maximization), ECM(NR)(the Newton-Raphson method is adapted to the ECM) and ECME(Expectation/Conditional Maximization Either). Since the algorithms are based on the EM algorithm, they also have EM’s main advantages, namely, stability and ease of implementation. Further details and explanations of the algorithms can be found in Zhao et al. (2020) <doi: 10.1016/j.csda.2020.106930>.
Author: Kexuan Yang <717260446@qq.com>, Sang Kyu Lee <leesa111@msu.edu>, Zhao Jun <zhaojun2021@hotmail.com>, and Hyoung-Moon Kim <hmk966a@gmail.com >
Maintainer: Sang Kyu Lee <leesa111@msu.edu>

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Package BGGM updated to version 2.0.0 with previous version 1.0.0 dated 2020-02-06

Title: Bayesian Gaussian Graphical Models
Description: Fit Bayesian Gaussian graphical models. The methods are separated into two Bayesian approaches for inference: hypothesis testing and estimation. There are extensions for confirmatory hypothesis testing, comparing Gaussian graphical models, and node wise predictability. These methods were recently introduced in the Gaussian graphical model literature, including Williams (2019) <doi:10.31234/osf.io/x8dpr>, Williams and Mulder (2019) <doi:10.31234/osf.io/ypxd8>, Williams, Rast, Pericchi, and Mulder (2019) <doi:10.31234/osf.io/yt386>.
Author: Donald Williams [aut, cre], Joris Mulder [aut]
Maintainer: Donald Williams <drwwilliams@ucdavis.edu>

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Package sars updated to version 1.2.3 with previous version 1.2.1 dated 2020-01-07

Title: Fit and Compare Species-Area Relationship Models Using Multimodel Inference
Description: Implements the basic elements of the multi-model inference paradigm for up to twenty species-area relationship models (SAR), using simple R list-objects and functions, as in Triantis et al. 2012 <DOI:10.1111/j.1365-2699.2011.02652.x>. The package is scalable and users can easily create their own model and data objects. Additional SAR related functions are provided.
Author: Thomas J. Matthews [aut, cre] (<https://orcid.org/0000-0002-7624-244X>), Francois Guilhaumon [aut] (<https://orcid.org/0000-0003-4707-8932>), Kevin Cazelles [rev] (<https://orcid.org/0000-0001-6619-9874>)
Maintainer: Thomas J. Matthews <txm676@gmail.com>

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Package lessR updated to version 3.9.5 with previous version 3.9.4 dated 2020-05-07

Title: Less Code, More Results
Description: Each function accomplishes the work of several or more standard R functions. For example, two function calls, Read() and CountAll(), read the data and generate summary statistics for all variables in the data frame, plus histograms and bar charts as appropriate. Other functions provide for descriptive statistics, a comprehensive regression analysis, analysis of variance and t-test, plotting including the introduced here Violin/Box/Scatter plot for a numerical variable, bar chart, histogram, box plot, density curves, calibrated power curve, reading multiple data formats with the same function call, variable labels, color themes, Trellis graphics and a built-in help system. Also includes a confirmatory factor analysis of multiple indicator measurement models, pedagogical routines for data simulation such as for the Central Limit Theorem, and generation and rendering of R markdown instructions for interpretative output.
Author: David Gerbing, The School of Business, Portland State University
Maintainer: David W. Gerbing <gerbing@pdx.edu>

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Package smoothedLasso updated to version 1.1 with previous version 1.0 dated 2020-04-03

Title: Smoothed LASSO Regression via Nesterov Smoothing
Description: We provide full functionality to compute smoothed LASSO regression estimates. For this, the LASSO objective function is first smoothed using Nesterov smoothing (see Y. Nesterov (2005) <doi:10.1007/s10107-004-0552-5>), resulting in a modified LASSO objective function with explicit gradients everywhere. The smoothed objective function and its gradient are used to minimize it via BFGS, and the obtained minimizer is returned. Using Nesterov smoothing, the smoothed LASSO objective function can be made arbitrarily close to the original (unsmoothed) one. In particular, the Nesterov approach has the advantage that it comes with explicit accuracy bounds, both on the L1/L2 difference of the unsmoothed to the smoothed LASSO objective function as well as on their respective minimizers. A progressive smoothing approach is provided which iteratively smoothes the LASSO, resulting in more stable regression estimates.
Author: Georg Hahn [aut,cre], Sharon M. Lutz [ctb], Nilanjana Laha [ctb], Christoph Lange [ctb]
Maintainer: Georg Hahn <ghahn@hsph.harvard.edu>

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Package spmoran updated to version 0.2.0-1 with previous version 0.2.0 dated 2020-05-20

Title: Moran Eigenvector-Based Scalable Spatial Additive Mixed Modeling
Description: Functions for estimating Moran eigenvector-based spatial additive mixed models, and other spatial regression models. For details see Murakami (2020) <arXiv:1703.04467>.
Author: Daisuke Murakami
Maintainer: Daisuke Murakami <dmuraka@ism.ac.jp>

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Package RDFTensor updated to version 1.2 with previous version 1.1 dated 2019-01-11

Title: Different Tensor Factorization (Decomposition) Techniques for RDF Tensors (Three-Mode-Tensors)
Description: Different Tensor Factorization techniques suitable for RDF Tensors. RDF Tensors are three-mode-tensors, binary tensors and usually very sparse. Currently implemented methods are 'RESCAL' Maximilian Nickel, Volker Tresp, and Hans-Peter Kriegel (2012) <doi:10.1145/2187836.2187874>, 'NMU' Daniel D. Lee and H. Sebastian Seung (1999) <doi:10.1038/44565>, 'ALS', Alternating Least Squares 'parCube' Papalexakis, Evangelos, C. Faloutsos, and N. Sidiropoulos (2012) <doi:10.1007/978-3-642-33460-3_39>, 'CP_APR' C. Chi and T. G. Kolda (2012) <doi.org/10.1137/110859063>. The code is mostly converted from MATLAB and Python implementations of these methods. The package also contains functions to get Boolean (Binary) transformation of the real-number-decompositions. These methods also are for general tensors, so with few modifications they can be applied for other types of tensor.
Author: Abdelmoneim Amer Desouki
Maintainer: Abdelmoneim Amer Desouki <desouki@mail.upb.de>

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Package ggasym updated to version 0.1.4 with previous version 0.1.3 dated 2020-04-03

Title: Asymmetric Matrix Plotting in 'ggplot2'
Description: Plots a symmetric matrix with three different fill aesthetics for the top-left and bottom-right triangles and along the diagonal. It operates within the Grammar of Graphics paradigm implemented in 'ggplot2'.
Author: Joshua H Cook [aut, cre] (<https://orcid.org/0000-0001-9815-6879>)
Maintainer: Joshua H Cook <joshuacook0023@gmail.com>

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New package glmm with initial version 1.4
Package: glmm
Type: Package
Title: Generalized Linear Mixed Models via Monte Carlo Likelihood Approximation
Version: 1.4
Date: 2020-5-24
Authors@R: c(person("Christina", "Knudson", role = c("aut", "cre"), email = "knud8583@stthomas.edu"), person("Charles J.", "Geyer", role = "ctb", email = "geyer@umn.edu"), person("Sydney", "Benson", role = "ctb", email = "bens0643@umn.edu"))
Maintainer: Christina Knudson <knud8583@stthomas.edu>
Description: Approximates the likelihood of a generalized linear mixed model using Monte Carlo likelihood approximation. Then maximizes the likelihood approximation to return maximum likelihood estimates, observed Fisher information, and other model information.
License: GPL-2
Depends: R (>= 3.5), trust, mvtnorm, Matrix, parallel, doParallel
Imports: stats, foreach, itertools, utils
ByteCompile: TRUE
NeedsCompilation: yes
Suggests: knitr
RoxygenNote: 7.0.2
Packaged: 2020-05-24 20:40:44 UTC; admin
Author: Christina Knudson [aut, cre], Charles J. Geyer [ctb], Sydney Benson [ctb]
Repository: CRAN
Date/Publication: 2020-05-31 10:30:02 UTC

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Package europepmc updated to version 0.4 with previous version 0.3 dated 2018-04-20

Title: R Interface to the Europe PubMed Central RESTful Web Service
Description: An R Client for the Europe PubMed Central RESTful Web Service (see <https://europepmc.org/RestfulWebService> for more information). It gives access to both metadata on life science literature and open access full texts. Europe PMC indexes all PubMed content and other literature sources including Agricola, a bibliographic database of citations to the agricultural literature, or Biological Patents. In addition to bibliographic metadata, the client allows users to fetch citations and reference lists. Links between life-science literature and other EBI databases, including ENA, PDB or ChEMBL are also accessible. No registration or API key is required. See the vignettes for usage examples.
Author: Najko Jahn [aut, cre, cph], Maëlle Salmon [ctb]
Maintainer: Najko Jahn <najko.jahn@gmail.com>

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New package AmpGram with initial version 1.0
Package: AmpGram
Type: Package
Title: Prediction of Antimicrobial Peptides
Version: 1.0
LazyData: TRUE
Date: 2020-05-19
Authors@R: c(person("Michal", "Burdukiewicz", email = "michalburdukiewicz@gmail.com", comment = c(ORCID = "0000-0001-8926-582X"), role = c("cre", "aut")), person("Katarzyna", "Sidorczuk", email = "sidorczuk.katarzyna17@gmail.com", role = c("ctb")), person("Filip", "Pietluch", email = "fpietluch@gmail.com", role = c("ctb")), person("Dominik", "Rafacz", email = "dominikrafacz@gmail.com", role = c("aut")), person("Stefan", "Roediger", email = "stefan.roediger@b-tu.de", comment = c(ORCID = "0000-0002-1441-6512"), role = c("ctb")), person("Jaroslaw", "Chilimoniuk", email = "jaroslaw.chilimoniuk@gmail.com", comment = c(ORCID = "0000-0001-5467-018X"), role = c("ctb")))
Description: Predicts antimicrobial peptides using random forests trained on the n-gram encoded peptides. The implemented algorithm can be accessed from both the command line and shiny-based GUI. The AmpGram model is too large for CRAN and it has to be downloaded separately from the repository: <https://github.com/michbur/AmpGramModel>.
License: GPL-3
URL: https://github.com/michbur/AmpGram
BugReports: https://github.com/michbur/AmpGram/issues
Encoding: UTF-8
Depends: R (>= 3.5.0)
Imports: biogram, devtools, pbapply, ranger, shiny, stringi
Suggests: DT, ggplot2, pander, rmarkdown, shinythemes, spelling
Repository: CRAN
RoxygenNote: 7.1.0
Language: en-US
NeedsCompilation: no
Packaged: 2020-05-22 11:38:49 UTC; michal
Author: Michal Burdukiewicz [cre, aut] (<https://orcid.org/0000-0001-8926-582X>), Katarzyna Sidorczuk [ctb], Filip Pietluch [ctb], Dominik Rafacz [aut], Stefan Roediger [ctb] (<https://orcid.org/0000-0002-1441-6512>), Jaroslaw Chilimoniuk [ctb] (<https://orcid.org/0000-0001-5467-018X>)
Maintainer: Michal Burdukiewicz <michalburdukiewicz@gmail.com>
Date/Publication: 2020-05-31 10:10:03 UTC

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New package universals with initial version 0.0.1
Package: universals
Title: S3 Generics for Bayesian Analyses
Version: 0.0.1
Authors@R: c(person(given = "Joe", family = "Thorley", role = c("aut", "cre"), email = "joe@poissonconsulting.ca", comment = c(ORCID = "0000-0002-7683-4592")), person(given = "Poisson Consulting", role = c("cph", "fnd")))
Description: Provides S3 generic methods and some default implementations for Bayesian analyses that generate Markov Chain Monte Carlo (MCMC) samples. The purpose of 'universals' is to reduce package dependencies and conflicts. The 'nlist' package implements all the methods for its 'nlists' class.
License: MIT + file LICENSE
URL: https://github.com/poissonconsulting/universals
BugReports: https://github.com/poissonconsulting/universals/issues
Depends: R (>= 3.3)
Suggests: covr, testthat
Encoding: UTF-8
Language: en-US
LazyData: true
RoxygenNote: 7.1.0
NeedsCompilation: no
Packaged: 2020-05-19 22:07:23 UTC; joe
Author: Joe Thorley [aut, cre] (<https://orcid.org/0000-0002-7683-4592>), Poisson Consulting [cph, fnd]
Maintainer: Joe Thorley <joe@poissonconsulting.ca>
Repository: CRAN
Date/Publication: 2020-05-31 09:50:02 UTC

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New package TwitterAutomatedTrading with initial version 0.1.0
Package: TwitterAutomatedTrading
Type: Package
Title: Automated Trading Using Tweets
Version: 0.1.0
Author: Lucas Godeiro
Maintainer: Lucas Godeiro <lucas.godeiro@hotmail.com>
Description: Provides an integration to the 'metatrader 5'. The functionalities carry out automated trading using sentiment indexes computed from 'twitter' and/or 'stockwits'. The sentiment indexes are based on the ph.d. dissertation "Essays on Economic Forecasting Models" (Godeiro,2018) <https://repositorio.ufpb.br/jspui/handle/123456789/15198> The integration between the 'R' and the 'metatrader 5' allows sending buy/sell orders to the brokerage.
License: GPL-3
Encoding: UTF-8
LazyData: true
Depends: R (>= 3.1.0)
RoxygenNote: 7.1.0
URL: https://github.com/lucasgodeiro/TwitterAutomatedTrading
BugReports: https://github.com/lucasgodeiro/TwitterAutomatedTrading/issues
Suggests: knitr, rmarkdown, covr
VignetteBuilder: knitr
Imports: curl, dplyr, jsonlite, lubridate, plyr, purrr, tibble, twitteR, naptime, utils, tidytext, magrittr
NeedsCompilation: no
Packaged: 2020-05-13 15:52:02 UTC; Cliente
Repository: CRAN
Date/Publication: 2020-05-31 09:50:13 UTC

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New package stringfish with initial version 0.11
Package: stringfish
Title: Alt String Implementation
Version: 0.11
Authors@R: c( person("Travers", "Ching", email = "traversc@gmail.com", role = c("aut", "cre", "cph")), person("Phillip", "Hazel", role = c("ctb"), comment = "Bundled PCRE2 code"), person("Zoltan", "Herczeg", role = c("ctb", "cph"), comment = "Bundled PCRE2 code"), person("University of Cambridge", role = c("cph"), comment = "Bundled PCRE2 code"), person("Tilera Corporation", role = c("cph"), comment = "Stack-less Just-In-Time compiler bundled with PCRE2"))
Maintainer: Travers Ching <traversc@gmail.com>
Description: Provides an extendable and performant 'alt-string' implementation backed by 'C++' vectors and strings.
License: GPL-3
Biarch: true
Encoding: UTF-8
Depends: R (>= 3.5.0)
SystemRequirements: C++11
LinkingTo: Rcpp (>= 0.12.18.3)
Imports: Rcpp
Suggests: qs, knitr, rmarkdown
VignetteBuilder: knitr
RoxygenNote: 7.1.0
Copyright: Copyright for the bundled 'PCRE2' library is held by University of Cambridge, Zoltan Herczeg and Tilera Coporation (Stack-less Just-In-Time compiler).
URL: https://github.com/traversc/stringfish
BugReports: https://github.com/traversc/stringfish/issues
NeedsCompilation: yes
Packaged: 2020-05-14 08:19:19 UTC; tching
Author: Travers Ching [aut, cre, cph], Phillip Hazel [ctb] (Bundled PCRE2 code), Zoltan Herczeg [ctb, cph] (Bundled PCRE2 code), University of Cambridge [cph] (Bundled PCRE2 code), Tilera Corporation [cph] (Stack-less Just-In-Time compiler bundled with PCRE2)
Repository: CRAN
Date/Publication: 2020-05-31 09:50:07 UTC

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New package quantilogram with initial version 2.0.1
Package: quantilogram
Title: Cross-Quantilogram
Version: 2.0.1
Authors@R: c(person(given = "Tatsushi", family = "Oka", role = c("aut", "cre"), email = "oka.econ@gmail.com"), person(given = "Heejon", family = "Han", role = "ctb"), person(given = "Oliver", family = "Linton", role = "ctb"), person(given = "Yoon-Jae", family = "Whang", role = "ctb"))
Maintainer: Tatsushi Oka <oka.econ@gmail.com>
Description: Estimation and inference methods for the cross-quantilogram. The cross-quantilogram is a measure of nonlinear dependence between two variables, based on either unconditional or conditional quantile functions. The cross-quantilogram can be considered as an extension of the correlogram, which is a correlation function over multiple lag periods and mainly focuses on linear dependency. One can use the cross-quantilogram to detect the presence of directional predictability from one time series to another. This package provides a statistical inference method based on the stationary bootstrap. See Linton and Whang (2007) <doi:10.1016/j.jeconom.2007.01.004> for univariate time series analysis and Han, Linton, Oka and Whang (2016) <doi:10.1016/j.jeconom.2016.03.001> for multivariate time series analysis.
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.0
Imports: quantreg, SparseM, stats, np
Depends: R (>= 2.10)
NeedsCompilation: no
Packaged: 2020-05-13 08:29:15 UTC; student-t
Author: Tatsushi Oka [aut, cre], Heejon Han [ctb], Oliver Linton [ctb], Yoon-Jae Whang [ctb]
Repository: CRAN
Date/Publication: 2020-05-31 10:00:03 UTC

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New package pbixr with initial version 0.1.3
Package: pbixr
Type: Package
Title: Access Data and Metadata from 'Microsoft' 'Power BI' Documents
Version: 0.1.3
Author: Don Diproto [aut, cre]
Maintainer: Don Diproto <package.pbixr@gmail.com>
Description: Access data and metadata from 'Microsoft' 'Power BI' ('.pbix', <https://powerbi.microsoft.com>) documents with R. The 'pbixr' package enables one to extract 'Power Query M' formulas (<https://docs.microsoft.com/en-us/power-query/>) and 'Data Analysis Expressions' ('DAX', <https://docs.microsoft.com/en-us/dax/>) queries and their properties, report layout and style, and data and data models.
URL: https://github.com/pbixr/pbixr
BugReports: https://github.com/pbixr/pbixr/issues
Depends: R (>= 3.2.0), dplyr
License: GPL-3
Encoding: UTF-8
LazyData: true
Imports: formatR, xml2, jsonlite, zip, utils, textclean, stringr
Suggests: knitr, rmarkdown, testthat (>= 2.1.0), RCurl, ggplot2, ggraph, igraph, imager, tidyr
VignetteBuilder: knitr
RoxygenNote: 7.0.0
SystemRequirements: 'Microsoft' 'PowerShell' (<https://docs.microsoft.com/en-us/powershell/>), 'Microsoft' 'Power BI' (<https://powerbi.microsoft.com>)
NeedsCompilation: no
Packaged: 2020-05-16 21:13:15 UTC; VIP
Repository: CRAN
Date/Publication: 2020-05-31 09:50:10 UTC

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New package knockoff with initial version 0.3.2
Package: knockoff
Type: Package
Title: The Knockoff Filter for Controlled Variable Selection
Version: 0.3.2
Date: 2018-09-15
Authors@R: c(person("Rina", "Foygel Barber", role = c("ctb"), comment="Development of the original Fixed-X Knockoffs"), person("Emmanuel", "Candes", role = c("ctb"), comment="Development of Model-X Knockoffs and original Fixed-X Knockoffs"), person("Lucas", "Janson", role = c("ctb"), comment="Development of Model-X Knockoffs"), person("Evan", "Patterson", role = c("aut"), comment="Original R package for the original Fixed-X Knockoffs"), person("Matteo", "Sesia", role = c("aut","cre"), comment="R package for Model-X Knockoffs", email="msesia@stanford.edu"))
Description: The knockoff filter is a general procedure for controlling the false discovery rate (FDR) when performing variable selection. For more information, see the website below and the accompanying paper: Candes et al., "Panning for Gold: Model-X Knockoffs for High-dimensional Controlled Variable Selection", 2016, <arXiv:1610.02351>.
License: GPL-3
URL: https://web.stanford.edu/group/candes/knockoffs/index.html
Depends: methods, stats
Imports: Rdsdp, Matrix, corpcor, glmnet, RSpectra, gtools, utils
Suggests: knitr, testthat, rmarkdown, lars, ranger, stabs, flare, doMC, parallel
RoxygenNote: 6.0.1
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2018-09-15 21:03:11 UTC; msesia
Author: Rina Foygel Barber [ctb] (Development of the original Fixed-X Knockoffs), Emmanuel Candes [ctb] (Development of Model-X Knockoffs and original Fixed-X Knockoffs), Lucas Janson [ctb] (Development of Model-X Knockoffs), Evan Patterson [aut] (Original R package for the original Fixed-X Knockoffs), Matteo Sesia [aut, cre] (R package for Model-X Knockoffs)
Maintainer: Matteo Sesia <msesia@stanford.edu>
Repository: CRAN
Date/Publication: 2018-09-16 16:30:08 UTC

More information about knockoff at CRAN
Permanent link

Package MFKnockoffs (with last version 0.9.1) was removed from CRAN

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

2017-09-29 0.9.1
2017-07-08 0.9

Permanent link
Package equaltestMI (with last version 0.1.0) was removed from CRAN

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

2017-08-04 0.1.0

Permanent link
Package knockoff (with last version 0.3.2) was removed from CRAN

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

2018-09-16 0.3.2
2017-10-17 0.3.0
2015-04-15 0.2.1
2015-02-05 0.2
2014-12-20 0.1.1
2014-12-06 0.1

Permanent link
Package TreeBUGS updated to version 1.4.5 with previous version 1.4.4 dated 2019-12-05

Title: Hierarchical Multinomial Processing Tree Modeling
Description: User-friendly analysis of hierarchical multinomial processing tree (MPT) models that are often used in cognitive psychology. Implements the latent-trait MPT approach (Klauer, 2010) <DOI:10.1007/s11336-009-9141-0> and the beta-MPT approach (Smith & Batchelder, 2010) <DOI:10.1016/j.jmp.2009.06.007> to model heterogeneity of participants. MPT models are conveniently specified by an .eqn-file as used by other MPT software and data are provided by a .csv-file or directly in R. Models are either fitted by calling JAGS or by an MPT-tailored Gibbs sampler in C++ (only for nonhierarchical and beta MPT models). Provides tests of heterogeneity and MPT-tailored summaries and plotting functions. A detailed documentation is available in Heck, Arnold, & Arnold (2018) <DOI:10.3758/s13428-017-0869-7>.
Author: Daniel W. Heck [aut, cre] (<https://orcid.org/0000-0002-6302-9252>), Nina R. Arnold [aut, dtc], Denis Arnold [aut], Alexander Ly [ctb], Marius Barth [ctb] (<https://orcid.org/0000-0002-3421-6665>)
Maintainer: Daniel W. Heck <dheck@uni-marburg.de>

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Package timetk updated to version 2.0.0 with previous version 1.0.0 dated 2020-04-19

Title: A Tool Kit for Working with Time Series in R
Description: Easy visualization, wrangling, and preprocessing of time series data for forecasting and machine learning prediction. Methods discussed herein are commonplace in machine learning, and have been cited in various literature. Refer to "Calendar Effects" in papers such as Taieb, Souhaib Ben. "Machine learning strategies for multi-step-ahead time series forecasting." Universit Libre de Bruxelles, Belgium (2014): 75-86. <http://souhaib-bentaieb.com/pdf/2014_phd.pdf>.
Author: Matt Dancho [aut, cre], Davis Vaughan [aut]
Maintainer: Matt Dancho <mdancho@business-science.io>

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Package taxlist updated to version 0.1.9 with previous version 0.1.8 dated 2020-04-29

Title: Handling Taxonomic Lists
Description: Handling taxonomic lists through objects of class 'taxlist'. This package provides functions to import species lists from 'Turboveg' (<https://www.synbiosys.alterra.nl/turboveg>) and the possibility to create backups from resulting R-objects. Also quick displays are implemented as summary-methods.
Author: Miguel Alvarez [aut, cre] (<https://orcid.org/0000-0003-1500-1834>), Zachary Foster [ctb] (<https://orcid.org/0000-0002-5075-0948>)
Maintainer: Miguel Alvarez <kamapu78@gmail.com>

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Permanent link

Package rmarkdown updated to version 2.2 with previous version 2.1 dated 2020-01-20

Title: Dynamic Documents for R
Description: Convert R Markdown documents into a variety of formats.
Author: JJ Allaire [aut], Yihui Xie [aut, cre] (<https://orcid.org/0000-0003-0645-5666>), Jonathan McPherson [aut], Javier Luraschi [aut], Kevin Ushey [aut], Aron Atkins [aut], Hadley Wickham [aut], Joe Cheng [aut], Winston Chang [aut], Richard Iannone [aut] (<https://orcid.org/0000-0003-3925-190X>), Andrew Dunning [ctb] (<https://orcid.org/0000-0003-0464-5036>), Atsushi Yasumoto [ctb] (<https://orcid.org/0000-0002-8335-495X>), Barret Schloerke [ctb], Christophe Dervieux [ctb], Frederik Aust [ctb] (<https://orcid.org/0000-0003-4900-788X>), Jeff Allen [ctb], JooYoung Seo [ctb] (<https://orcid.org/0000-0002-4064-6012>), Malcolm Barrett [ctb], Rob Hyndman [ctb], Romain Lesur [ctb], Roy Storey [ctb], Ruben Arslan [ctb], Sergio Oller [ctb], RStudio, PBC [cph], jQuery Foundation [cph] (jQuery library), jQuery contributors [ctb, cph] (jQuery library; authors listed in inst/rmd/h/jquery-AUTHORS.txt), jQuery UI contributors [ctb, cph] (jQuery UI library; authors listed in inst/rmd/h/jqueryui-AUTHORS.txt), Mark Otto [ctb] (Bootstrap library), Jacob Thornton [ctb] (Bootstrap library), Bootstrap contributors [ctb] (Bootstrap library), Twitter, Inc [cph] (Bootstrap library), Alexander Farkas [ctb, cph] (html5shiv library), Scott Jehl [ctb, cph] (Respond.js library), Ivan Sagalaev [ctb, cph] (highlight.js library), Greg Franko [ctb, cph] (tocify library), John MacFarlane [ctb, cph] (Pandoc templates), Google, Inc. [ctb, cph] (ioslides library), Dave Raggett [ctb] (slidy library), W3C [cph] (slidy library), Dave Gandy [ctb, cph] (Font-Awesome), Ben Sperry [ctb] (Ionicons), Drifty [cph] (Ionicons), Aidan Lister [ctb, cph] (jQuery StickyTabs), Benct Philip Jonsson [ctb, cph] (pagebreak lua filter), Albert Krewinkel [ctb, cph] (pagebreak lua filter)
Maintainer: Yihui Xie <xie@yihui.name>

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Package ipmisc updated to version 3.0.0 with previous version 2.0.0 dated 2020-04-11

Title: Miscellaneous Functions for Data Cleaning and Analysis
Description: Provides functions needed for data cleaning and formatting and forms data cleaning and wrangling backend for the following packages: 'broomExtra', 'ggstatsplot', 'groupedstats', 'pairwiseComparisons', 'statsExpressions', and 'tidyBF'.
Author: Indrajeet Patil [aut, cre, cph] (<https://orcid.org/0000-0003-1995-6531>)
Maintainer: Indrajeet Patil <patilindrajeet.science@gmail.com>

Diff between ipmisc versions 2.0.0 dated 2020-04-11 and 3.0.0 dated 2020-05-31

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Package Disequilibrium updated to version 1.1 with previous version 1.0 dated 2020-01-20

Title: Disequilibrium Models
Description: Estimate, summarize, and perform predictions with the market in disequilibrium model, as found in Gourieroux, C. (2000) <doi:10.1017/CBO9780511805608> and Maddala, G. (1983) <doi:10.1017/CBO9780511810176>. The parameters are estimated with maximum likelihood.
Author: Nate Latshaw [aut, cre], Michael Guggisberg [aut], Institute for Defense Analyses [cph]
Maintainer: Nate Latshaw <dcms2015@gmail.com>

Diff between Disequilibrium versions 1.0 dated 2020-01-20 and 1.1 dated 2020-05-31

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