Tue, 26 Jan 2021

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

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

2020-12-11 0.1.1
2019-12-06 0.1.0

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Package liquidSVM (with last version 1.2.4) was removed from CRAN

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

2019-09-14 1.2.4
2019-09-03 1.2.3

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Package wicket (with last version 0.4.0) was removed from CRAN

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

2017-11-19 0.4.0
2017-03-23 0.3.0
2017-01-21 0.2.0

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Package sensobol updated to version 1.0.0 with previous version 0.2.2 dated 2020-02-25

Title: Computation of Variance-Based Sensitivity Indices
Description: It allows to rapidly compute, bootstrap and plot up to third-order Sobol'-based sensitivity indices using several state-of-the-art first and total-order estimators. Sobol' indices can be computed either for models that yield a scalar as a model output or for systems of differential equations. The package also provides a suit of benchmark tests functions and several options to obtain publication-ready figures of the model output uncertainty and sensitivity-related analysis.
Author: Arnald Puy [aut, cre] (<https://orcid.org/0000-0001-9469-2156>), Bertrand Ioos [ctb] (Author of included 'sensitivity' fragments), Gilles Pujol [ctb] (Author of included 'sensitivity' fragments), RStudio [cph] (Copyright holder of included 'sensitivity' fragments)
Maintainer: Arnald Puy <arnald.puy@pm.me>

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Package polyCub updated to version 0.8.0 with previous version 0.7.1 dated 2019-02-07

Title: Cubature over Polygonal Domains
Description: Numerical integration of continuously differentiable functions f(x,y) over simple closed polygonal domains. The following cubature methods are implemented: product Gauss cubature (Sommariva and Vianello, 2007, <doi:10.1007/s10543-007-0131-2>), the simple two-dimensional midpoint rule (wrapping 'spatstat.geom' functions), adaptive cubature for radially symmetric functions via line integrate() along the polygon boundary (Meyer and Held, 2014, <doi:10.1214/14-AOAS743>, Supplement B), and integration of the bivariate Gaussian density based on polygon triangulation. For simple integration along the axes, the 'cubature' package is more appropriate.
Author: Sebastian Meyer [aut, cre, trl] (<https://orcid.org/0000-0002-1791-9449>), Leonhard Held [ths], Michael Hoehle [ths]
Maintainer: Sebastian Meyer <seb.meyer@fau.de>

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Package multiclassPairs updated to version 0.4.1 with previous version 0.4.0 dated 2020-11-20

Title: Build MultiClass Pair-Based Classifiers using TSPs or RF
Description: A toolbox to train a single sample classifier that uses in-sample feature relationships. The relationships are represented as feature1 < feature2 (e.g. gene1 < gene2). We provide two options to go with. First is based on 'switchBox' package which uses Top-score pairs algorithm. Second is a novel implementation based on random forest algorithm. For simple problems we recommend to use one-vs-rest using TSP option due to its simplicity and for being easy to interpret. For complex problems RF performs better. Both lines filter the features first then combine the filtered features to make the list of all the possible rules (i.e. rule1: feature1 < feature2, rule2: feature1 < feature3, etc...). Then the list of rules will be filtered and the most important and informative rules will be kept. The informative rules will be assembled in an one-vs-rest model or in an RF model. We provide a detailed description with each function in this package to explain the filtration and training methodology in each line.
Author: Nour-al-dain Marzouka
Maintainer: Nour-al-dain Marzouka <Nour-al-dain.Marzouka@med.lu.se>

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Package dMod updated to version 1.0.2 with previous version 1.0.1 dated 2020-02-10

Title: Dynamic Modeling and Parameter Estimation in ODE Models
Description: The framework provides functions to generate ODEs of reaction networks, parameter transformations, observation functions, residual functions, etc. The framework follows the paradigm that derivative information should be used for optimization whenever possible. Therefore, all major functions produce and can handle expressions for symbolic derivatives. The methods used in dMod were published in Kaschek et al, 2019, <doi:10.18637/jss.v088.i10>.
Author: Daniel Kaschek
Maintainer: Daniel Kaschek <daniel.kaschek@gmail.com>

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Package utile.visuals updated to version 0.3.0 with previous version 0.2.5 dated 2020-05-01

Title: Create Visuals for Publication
Description: A small set of functions to aid in the production of visuals in ggplot2. Includes minimalist themes with transparent backgrounds and a suite of tools for building survival curves with risk tables.
Author: Eric Finnesgard [aut, cre]
Maintainer: Eric Finnesgard <efinite@outlook.com>

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Package GPFDA updated to version 3.1.0 with previous version 3.0.0 dated 2021-01-11

Title: Gaussian Process for Functional Data Analysis
Description: Functionalities for modelling functional data with multidimensional inputs, multivariate functional data, and non-separable and/or non-stationary covariance structure of function-valued processes. In addition, there are functionalities for functional regression models where the mean function depends on scalar and/or functional covariates and the covariance structure depends on functional covariates. The development version of the package can be found on <https://github.com/gpfda/GPFDA-dev>.
Author: Jian Qing Shi, Yafeng Cheng, Evandro Konzen
Maintainer: Evandro Konzen <gpfda.r@gmail.com>

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Package qgcomp updated to version 2.7.0 with previous version 2.6.0 dated 2020-10-06

Title: Quantile G-Computation
Description: G-computation for a set of time-fixed exposures with quantile-based basis functions, possibly under linearity and homogeneity assumptions. This approach estimates a regression line corresponding to the expected change in the outcome (on the link basis) given a simultaneous increase in the quantile-based category for all exposures. Works with continuous, binary, and right-censored time-to-event outcomes. Reference: Alexander P. Keil, Jessie P. Buckley, Katie M. OBrien, Kelly K. Ferguson, Shanshan Zhao, and Alexandra J. White (2019) A quantile-based g-computation approach to addressing the effects of exposure mixtures; <doi:10.1289/EHP5838>.
Author: Alexander Keil [aut, cre]
Maintainer: Alexander Keil <akeil@unc.edu>

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Package bkmrhat updated to version 1.0.1 with previous version 1.0.0 dated 2020-10-12

Title: Parallel Chain Tools for Bayesian Kernel Machine Regression
Description: Bayesian kernel machine regression (from the 'bkmr' package) is a Bayesian semi-parametric generalized linear model approach under identity and probit links. There are a number of functions in this package that extend Bayesian kernel machine regression fits to allow multiple-chain inference and diagnostics, which leverage functions from the 'future', 'rstan', and 'coda' packages. Reference: Bobb, J. F., Henn, B. C., Valeri, L., & Coull, B. A. (2018). Statistical software for analyzing the health effects of multiple concurrent exposures via Bayesian kernel machine regression. ; <doi:10.1186/s12940-018-0413-y>.
Author: Alexander Keil [aut, cre]
Maintainer: Alexander Keil <akeil@unc.edu>

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Package ccmReportR updated to version 0.0.3 with previous version 0.0.2 dated 2021-01-19

Title: Wraps 'CCM' with Utility Functions
Description: Provides a set of functions to perform queries against the 'CCM' API <https://mohcontacttracing.my.salesforce.com>.
Author: James Lane [aut, cre]
Maintainer: James Lane <lanejames35@gmail.com>

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Package TreeTools updated to version 1.4.2 with previous version 1.4.1 dated 2020-12-09

Title: Create, Modify and Analyse Phylogenetic Trees
Description: Efficient implementations of functions for the creation, modification and analysis of phylogenetic trees. Applications include: generation of trees with specified shapes; analysis of tree shape; rooting of trees and extraction of subtrees; calculation and depiction of node support; calculation of ancestor-descendant relationships; import and export of trees from Newick, Nexus (Maddison et al. 1997) <doi:10.1093/sysbio/46.4.590>, and TNT <http://www.lillo.org.ar/phylogeny/tnt/> formats; and analysis of splits and cladistic information.
Author: Martin R. Smith [aut, cre, cph] (<https://orcid.org/0000-0001-5660-1727>), Emmanuel Paradis [cph] (<https://orcid.org/0000-0003-3092-2199>)
Maintainer: Martin R. Smith <martin.smith@durham.ac.uk>

Diff between TreeTools versions 1.4.1 dated 2020-12-09 and 1.4.2 dated 2021-01-26

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Package soilDB updated to version 2.5.9 with previous version 2.5.8 dated 2020-10-21

Title: Soil Database Interface
Description: A collection of functions for reading data from USDA-NCSS soil databases.
Author: Dylan Beaudette [aut], Jay Skovlin [aut], Stephen Roecker [aut], Andrew Brown [aut, cre]
Maintainer: Andrew Brown <andrew.g.brown@usda.gov>

Diff between soilDB versions 2.5.8 dated 2020-10-21 and 2.5.9 dated 2021-01-26

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More information about soilDB at CRAN
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Package memoise updated to version 2.0.0 with previous version 1.1.0 dated 2017-04-21

Title: Memoisation of Functions
Description: Cache the results of a function so that when you call it again with the same arguments it returns the pre-computed value.
Author: Hadley Wickham [aut], Jim Hester [aut, cre], Winston Chang [aut], Kirill Müller [aut], Daniel Cook [aut], Mark Edmondson [ctb]
Maintainer: Jim Hester <jim.hester@rstudio.com>

Diff between memoise versions 1.1.0 dated 2017-04-21 and 2.0.0 dated 2021-01-26

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New package MachineShop with initial version 2.6.1
Package: MachineShop
Type: Package
Title: Machine Learning Models and Tools
Version: 2.6.1
Date: 2021-01-25
Authors@R: person(c("Brian", "J"), "Smith", email = "brian-j-smith@uiowa.edu", role = c("aut", "cre"))
Author: Brian J Smith [aut, cre]
Maintainer: Brian J Smith <brian-j-smith@uiowa.edu>
Description: Meta-package for statistical and machine learning with a unified interface for model fitting, prediction, performance assessment, and presentation of results. Approaches for model fitting and prediction of numerical, categorical, or censored time-to-event outcomes include traditional regression models, regularization methods, tree-based methods, support vector machines, neural networks, ensembles, data preprocessing, filtering, and model tuning and selection. Performance metrics are provided for model assessment and can be estimated with independent test sets, split sampling, cross-validation, or bootstrap resampling. Resample estimation can be executed in parallel for faster processing and nested in cases of model tuning and selection. Modeling results can be summarized with descriptive statistics; calibration curves; variable importance; partial dependence plots; confusion matrices; and ROC, lift, and other performance curves.
Depends: R (>= 3.6.0)
Imports: abind, dials (>= 0.0.4), foreach, ggplot2 (>= 3.3.0), kernlab, magrittr, Matrix, methods, nnet, party, polspline, progress, recipes (>= 0.1.4), rlang, rsample, Rsolnp, survival, tibble, utils
Suggests: adabag, BART, bartMachine, C50, cluster, doParallel, e1071, earth, elasticnet, gbm, glmnet, gridExtra, Hmisc, kableExtra, kknn, knitr, lars, MASS, mboost, mda, partykit, pls, randomForest, randomForestSRC, ranger, rmarkdown, rms, rpart, testthat, tree, xgboost
LazyData: true
License: GPL-3
URL: https://brian-j-smith.github.io/MachineShop/
BugReports: https://github.com/brian-j-smith/MachineShop/issues
RoxygenNote: 7.1.1
VignetteBuilder: knitr
Encoding: UTF-8
NeedsCompilation: no
Packaged: 2021-01-25 20:20:59 UTC; bjsmith
Repository: CRAN
Date/Publication: 2021-01-26 17:40:08 UTC

More information about MachineShop at CRAN
Permanent link

Package diseq updated to version 0.1.1 with previous version 0.0.14 dated 2020-11-30

Title: Estimation Methods for Markets in Disequilibrium
Description: Provides estimation methods for markets in equilibrium and disequilibrium. Specifically, it supports the estimation of an equilibrium and four disequilibrium models with both correlated and independent shocks. It also provides post-estimation analysis tools, such as aggregation and marginal effects calculations. The estimation methods are based on full information maximum likelihood techniques given in Maddala and Nelson (1974) <doi:10.2307/1914215>. They are implemented using the analytic derivative expressions calculated in Karapanagiotis (2020) <doi:10.2139/ssrn.3525622>. The equilibrium estimation constitutes a special case of a system of simultaneous equations. The disequilibrium models, instead, replace the market clearing condition with a short side rule and allow for different specifications of price dynamics.
Author: Pantelis Karapanagiotis [aut, cre] (<https://orcid.org/0000-0001-9871-1908>)
Maintainer: Pantelis Karapanagiotis <pikappa.devel@gmail.com>

Diff between diseq versions 0.0.14 dated 2020-11-30 and 0.1.1 dated 2021-01-26

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Package cropDemand updated to version 1.0.1 with previous version 1.0.0 dated 2021-01-22

Title: Spatial Crop Water Demand for Brazil
Description: Estimation of crop water demand can be processed via this package. As example, the data from 'TerraClimate' dataset (<http://www.climatologylab.org/terraclimate.html>) calibrated with automatic weather stations of National Meteorological Institute of Brazil is available in a coarse spatial resolution to do the crop water demand. However, the user have also the option to download the variables directly from 'TerraClimate' repository with the download.terraclimate function and access the original 'TerraClimate' products. If the user believes that is necessary calibrate the variables, there is another function to do it. Lastly, the estimation of the crop water demand present in this package can be run for all the Brazilian territory with 'TerraClimate' dataset.
Author: Roberto Filgueiras [aut, cre] (<https://orcid.org/0000-0002-0186-8907>), Luan P. Venancio [aut] (<https://orcid.org/0000-0002-5544-8588>), Catariny C. Aleman [aut] (<https://orcid.org/0000-0002-3894-3077>), Fernando F. da Cunha [aut] (<https://orcid.org/0000-0002-1671-1021>)
Maintainer: Roberto Filgueiras <betofilgueiras@gmail.com>

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More information about cropDemand at CRAN
Permanent link

Package bayestestR updated to version 0.8.2 with previous version 0.8.0 dated 2020-12-05

Title: Understand and Describe Bayesian Models and Posterior Distributions
Description: Provides utilities to describe posterior distributions and Bayesian models. It includes point-estimates such as Maximum A Posteriori (MAP), measures of dispersion (Highest Density Interval - HDI; Kruschke, 2015 <doi:10.1016/C2012-0-00477-2>) and indices used for null-hypothesis testing (such as ROPE percentage, pd and Bayes factors).
Author: Dominique Makowski [aut, cre] (<https://orcid.org/0000-0001-5375-9967>), Daniel Lüdecke [aut] (<https://orcid.org/0000-0002-8895-3206>), Mattan S. Ben-Shachar [aut] (<https://orcid.org/0000-0002-4287-4801>), Michael D. Wilson [aut] (<https://orcid.org/0000-0003-4143-7308>), Paul-Christian Bürkner [rev], Tristan Mahr [rev] (<https://orcid.org/0000-0002-8890-5116>), Henrik Singmann [ctb] (<https://orcid.org/0000-0002-4842-3657>), Quentin F. Gronau [ctb] (<https://orcid.org/0000-0001-5510-6943>), Sam Crawley [ctb] (<https://orcid.org/0000-0002-7847-0411>)
Maintainer: Dominique Makowski <dom.makowski@gmail.com>

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Package withr updated to version 2.4.1 with previous version 2.4.0 dated 2021-01-15

Title: Run Code 'With' Temporarily Modified Global State
Description: A set of functions to run code 'with' safely and temporarily modified global state. Many of these functions were originally a part of the 'devtools' package, this provides a simple package with limited dependencies to provide access to these functions.
Author: Jim Hester [aut, cre], Kirill Müller [aut], Kevin Ushey [aut], Hadley Wickham [aut], Winston Chang [aut], Jennifer Bryan [ctb], Richard Cotton [ctb], RStudio [cph]
Maintainer: Jim Hester <jim.hester@rstudio.com>

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Package onlineretail updated to version 0.1.1 with previous version 0.1.0 dated 2020-11-20

Title: Online Retail Dataset
Description: Transactions occurring for a UK-based and registered, non-store online retail between 01/12/2010 and 09/12/2011 (Chen et. al., 2012, <doi:10.1145/1835804.1835882>). This dataset is included in this package with the donor's permission, Dr. Daqing Chen.
Author: Allan Quadros [aut, cre] (<https://orcid.org/0000-0003-3250-5380>)
Maintainer: Allan Quadros <allanvcq@gmail.com>

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Package GB2group updated to version 0.3.0 with previous version 0.2.0 dated 2019-02-21

Title: Estimation of the Generalised Beta Distribution of the Second Kind from Grouped Data
Description: Estimation of the generalized beta distribution of the second kind (GB2) and related models using grouped data in form of income shares. The GB2 family is a general class of distributions that provides an accurate fit to income data. 'GB2group' includes functions to estimate the GB2, the Singh-Maddala, the Dagum, the Beta 2, the Lognormal and the Fisk distributions. 'GB2group' deploys two different econometric strategies to estimate these parametric distributions, the equally weighted minimum distance (EWMD) estimator and the optimally weighted minimum distance (OMD) estimator. Asymptotic standard errors are reported for the OMD estimates. Standard errors of the EWMD estimates are obtained by Monte Carlo simulation. See Jorda et al. (2018) <arXiv:1808.09831> for a detailed description of the estimation procedure.
Author: Vanesa Jorda <jordav@unican.es>, Jose Maria Sarabia <jose.sarabia@unican.es>, Markus Jäntti <markus.jantti@sofi.su.se>.
Maintainer: Vanesa Jorda <jordav@unican.es>

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Package brxx updated to version 0.1.2 with previous version 0.1.1 dated 2020-12-02

Title: Bayesian Test Reliability Estimation
Description: When samples contain missing data, are small, or are suspected of bias, estimation of scale reliability may not be trustworthy. A recommended solution for this common problem has been Bayesian model estimation. Bayesian methods rely on user specified information from historical data or researcher intuition to more accurately estimate the parameters. This package provides a user friendly interface for estimating test reliability. Here, reliability is modeled as a beta distributed random variable with shape parameters alpha=true score variance and beta=error variance (Tanzer & Harlow, 2020) <doi:10.1080/00273171.2020.1854082>.
Author: Joshua Ray Tanzer
Maintainer: Joshua Ray Tanzer <jtanzer@lifespan.org>

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Package leiden updated to version 0.3.7 with previous version 0.3.6 dated 2020-12-07

Title: R Implementation of Leiden Clustering Algorithm
Description: Implements the 'Python leidenalg' module to be called in R. Enables clustering using the leiden algorithm for partition a graph into communities. See the 'Python' repository for more details: <https://github.com/vtraag/leidenalg> Traag et al (2018) From Louvain to Leiden: guaranteeing well-connected communities. <arXiv:1810.08473>.
Author: S. Thomas Kelly [aut, cre, trl], Vincent A. Traag [com]
Maintainer: S. Thomas Kelly <tom.kelly@riken.jp>

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Package subscreen updated to version 3.0.3 with previous version 3.0.2 dated 2020-12-03

Title: Systematic Screening of Study Data for Subgroup Effects
Description: Identifying outcome relevant subgroups has now become as simple as possible! The formerly lengthy and tedious search for the needle in a haystack will be replaced by a single, comprehensive and coherent presentation. The central result of a subgroup screening is a diagram in which each single dot stands for a subgroup. The diagram may show thousands of them. The position of the dot in the diagram is determined by the sample size of the subgroup and the statistical measure of the treatment effect in that subgroup. The sample size is shown on the horizontal axis while the treatment effect is displayed on the vertical axis. Furthermore, the diagram shows the line of no effect and the overall study results. For small subgroups, which are found on the left side of the plot, larger random deviations from the mean study effect are expected, while for larger subgroups only small deviations from the study mean can be expected to be chance findings. So for a study with no conspicuous subgroup effects, the dots in the figure are expected to form a kind of funnel. Any deviations from this funnel shape hint to conspicuous subgroups. This approach was presented in Muysers (2020) <doi:10.1007/s43441-019-00082-6> and referenced in Ballarini (2020) <doi:10.1002/pst.2012>. New to version 3 is the Automatic Screening of one- or MUlti-factorial Subgroups (ASMUS) for documentation of the structured review of subgroup findings.
Author: Bodo Kirsch, Steffen Jeske, Susanne Lippert, Thomas Schmelter, Christoph Muysers, Hermann Kulmann
Maintainer: Bodo Kirsch <bodo.kirsch@bayer.com>

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Package openSkies updated to version 1.0.0 with previous version 0.99.8 dated 2020-12-04

Title: An R Client-Side Interface to the 'OpenSky' API
Description: Provides functionalities and data structures to retrieve, analyze and visualize aviation data. It includes a client interface to the 'OpenSky' API <https://opensky-network.org>. It allows retrieval of flight information, as well as aircraft state vectors.
Author: Rafael Ayala, Daniel Ayala, David Ruiz, Aleix Sellés, Lara Sellés Vidal
Maintainer: Rafael Ayala <r.ayala14@imperial.ac.uk>

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New package MMD with initial version 1.0.0
Package: MMD
Type: Package
Title: Minimal Multilocus Distance (MMD) for Source Attribution and Loci Selection
Imports: e1071, plyr, bigmemory
Version: 1.0.0
Authors@R: person("Francisco", "Perez-Reche", email = "fperez-reche@abdn.ac.uk", role = c("aut", "cre"))
Maintainer: Francisco Perez-Reche <fperez-reche@abdn.ac.uk>
Description: The aim of the package is two-fold: (i) To implement the MMD method for attribution of individuals to sources using the Hamming distance between multilocus genotypes. (ii) To select informative genetic markers based on information theory concepts (entropy, mutual information and redundancy). The package implements the functions introduced by Perez-Reche, F. J., Rotariu, O., Lopes, B. S., Forbes, K. J. and Strachan, N. J. C. Mining whole genome sequence data to efficiently attribute individuals to source populations. Scientific Reports 10, 12124 (2020) <doi:10.1038/s41598-020-68740-6>. See more details and examples in the README file.
License: GPL-3
Encoding: UTF-8
LazyData: true
Suggests: knitr, rmarkdown
VignetteBuilder: knitr
RoxygenNote: 7.1.0
NeedsCompilation: no
Packaged: 2021-01-23 10:50:41 UTC; s05fp2
Author: Francisco Perez-Reche [aut, cre]
Repository: CRAN
Date/Publication: 2021-01-26 13:40:08 UTC

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New package GWI with initial version 1.0.0
Package: GWI
Title: Count and Continuous Generalized Variability Indexes
Version: 1.0.0
Authors@R: c(person("Aboubacar Y.", "Touré", email = "aboubacaryacoubatoure.ussgb@gmail.com", role = "aut"), person("Célestin C.", "Kokonendji", role = "aut"), person("Aboubacar Y.", "Touré", email = "aboubacaryacoubatoure.ussgb@gmail.com", role = "cre"))
Description: Univariate Poisson dispersion index (DI) for count data, univariate exponential variation index (VI) for positive continuous data functions are performed. Also, the generalized dispersion index (GDI) and the marginal dispersion index (MDI) functions are carried out. Finally, the generalized variation index (GVI) and the marginal variation index (MVI) functions are computed. See Abid et al. (2020), Fisher (1934), Kokonendji and Puig (2018), Kokonendji et al. (2020) and Touré et al. (2020) for more details on these indexes.
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.1
NeedsCompilation: no
Packaged: 2021-01-23 12:16:50 UTC; PC
Author: Aboubacar Y. Touré [aut], Célestin C. Kokonendji [aut], Aboubacar Y. Touré [cre]
Maintainer: Aboubacar Y. Touré <aboubacaryacoubatoure.ussgb@gmail.com>
Repository: CRAN
Date/Publication: 2021-01-26 13:50:05 UTC

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New package gfilogisreg with initial version 1.0.0
Package: gfilogisreg
Title: Generalized Fiducial Inference for Binary Logistic Regression Models
Version: 1.0.0
Authors@R: person(given = "Stéphane", family = "Laurent", role = c("aut", "cre"), email = "laurent_step@outlook.fr")
Description: Fiducial framework for the logistic regression model. The fiducial distribution of the parameters of the logistic regression is simulated, allowing to perform statistical inference on any parameter of interest. The algorithm is taken from Jessi Cisewski's PhD thesis: Jessi Cisewski (2012), "Generalized fiducial inference for mixed linear models".
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.1
SystemRequirements: C++11, gmp
Imports: rcdd, lazyeval, spatstat, EigenR, stats, Rcpp
LinkingTo: Rcpp, RcppArmadillo, roptim, BH
Suggests: knitr, rmarkdown
VignetteBuilder: knitr
NeedsCompilation: yes
Packaged: 2021-01-23 10:02:55 UTC; stla
Author: Stéphane Laurent [aut, cre]
Maintainer: Stéphane Laurent <laurent_step@outlook.fr>
Repository: CRAN
Date/Publication: 2021-01-26 13:30:02 UTC

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New package dataquieR with initial version 1.0.3
Package: dataquieR
Title: Data Quality in Epidemiological Research
Version: 1.0.3
Authors@R: c(person(given = "Adrian", family = "Richter", role = "aut", email = "richtera@uni-greifswald.de"), person(given = "Carsten Oliver", family = "Schmidt", role = "aut", email = "carsten.schmidt@uni-greifswald.de"), person(given = "Stephan", family = "Struckmann", role = c("aut", "cre"), email = "stephan.struckmann@uni-greifswald.de"))
Description: A set of functions to assess data quality issues in studies. See 'TMF' <https://www.tmf-ev.de/EnglishSite/Home.aspx> guideline and 'DFG' <https://www.dfg.de/en/index.jsp> project at <https://dfg-qa.ship-med.uni-greifswald.de>.
License: CC BY 4.0
URL: https://dfg-qa.ship-med.uni-greifswald.de/
BugReports: https://gitlab.com/libreumg/dataquier/-/issues
Depends: R (>= 3.3.0)
Imports: MASS, MultinomialCI, R.devices, cowplot (>= 0.9.4), emmeans, ggplot2 (>= 2.1.0), ggpubr, lme4, lubridate, parallelMap, reshape, rlang, robustbase, dplyr (>= 1.0.2), utils
Suggests: htmltools, rmarkdown, knitr, DT (>= 0.15), digest, flexdashboard, anytime, patchwork, rstudioapi, testthat (>= 2.3.2), tibble, vdiffr
VignetteBuilder: knitr
Encoding: UTF-8
KeepSource: TRUE
Language: en-US
LazyData: true
RoxygenNote: 7.1.1
NeedsCompilation: no
Packaged: 2021-01-23 12:00:33 UTC; struckmanns
Author: Adrian Richter [aut], Carsten Oliver Schmidt [aut], Stephan Struckmann [aut, cre]
Maintainer: Stephan Struckmann <stephan.struckmann@uni-greifswald.de>
Repository: CRAN
Date/Publication: 2021-01-26 13:40:02 UTC

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New package verhoeff with initial version 0.4.0
Package: verhoeff
Type: Package
Title: Implementation of the 'Verhoeff' Check Digit Algorithm
Version: 0.4.0
Author: Conor Neilson
Maintainer: Conor Neilson <condwanaland@gmail.com>
Description: An implementation of the 'Verhoeff' algorithm for calculating check digits (Verhoeff, J. (1969) <doi:10.1002/zamm.19710510323>). Functions are provided to calculate a check digit given an input number, calculate and append a check digit to an input number, and validate that a check digit is correct given an input number.
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.1
Suggests: testthat, dplyr
NeedsCompilation: no
Packaged: 2021-01-22 21:25:33 UTC; conorneilson
Repository: CRAN
Date/Publication: 2021-01-26 12:20:02 UTC

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New package StratifiedSampling with initial version 0.1.0
Package: StratifiedSampling
Type: Package
Title: Different Methods for Stratified Sampling
Version: 0.1.0
Authors@R: c( person("Raphael", "Jauslin", email = "raphael.jauslin@unine.ch",role = c("aut", "cre"),comment = c(ORCID = "0000-0003-1088-3356")), person("Esther", "Eustache", email = "esther.eustache@unine.ch",role = c("aut")), person("Yves", "Tillé",role = c("aut"),comment = c(ORCID = "0000-0003-0904-5523")) )
Description: Integrating a stratified structure in the population in a sampling design can considerably reduce the variance of the Horvitz-Thompson estimator. We propose in this package different methods to handle the selection of a balanced sample in stratified population. For more details see Raphaël Jauslin, Esther Eustache and Yves Tillé (2021) <arXiv:2101.05568>.
License: GPL (>= 2)
Encoding: UTF-8
LazyData: true
LinkingTo: RcppArmadillo, Rcpp
Imports: Rcpp
Depends: Matrix, R (>= 3.5.0)
Suggests: knitr, rmarkdown, ggplot2, sampling, BalancedSampling, MASS, stats, testthat
RoxygenNote: 7.1.1
NeedsCompilation: yes
Packaged: 2021-01-22 09:34:23 UTC; jauslinr
Author: Raphael Jauslin [aut, cre] (<https://orcid.org/0000-0003-1088-3356>), Esther Eustache [aut], Yves Tillé [aut] (<https://orcid.org/0000-0003-0904-5523>)
Maintainer: Raphael Jauslin <raphael.jauslin@unine.ch>
Repository: CRAN
Date/Publication: 2021-01-26 12:20:06 UTC

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Permanent link

New package AlleleShift with initial version 0.9
Package: AlleleShift
Type: Package
Title: Predict and Visualize Population-Level Changes in Allele Frequencies in Response to Climate Change
Version: 0.9
Date: 2021-1-19
Author: Roeland Kindt [cre, aut] (<https://orcid.org/0000-0002-7672-0712>)
Authors@R: c(person(given = "Roeland", family = "Kindt", role = c("cre", "aut"), email = "R.KINDT@CGIAR.ORG", comment = c(ORCID = "0000-0002-7672-0712")))
Maintainer: Roeland Kindt <R.KINDT@CGIAR.ORG>
Description: Methods (Kindt, R. 2021. <doi:10.1101/2021.01.15.426775>) are provided of calibrating and predicting shifts in allele frequencies through redundancy analysis ('vegan::rda()') and generalized additive models ('mgcv::gam()'). Visualization functions for predicted changes in allele frequencies include 'shift.dot.ggplot()', 'shift.pie.ggplot()', 'shift.moon.ggplot()', 'shift.waffle.ggplot()' and 'shift.surf.ggplot()' that are made with input data sets that are prepared by helper functions for each visualization method. Examples in the documentation show how to prepare animated climate change graphics through a time series with the 'gganimate' package. Function 'amova.rda()' shows how Analysis of Molecular Variance can be directly conducted with the results from redundancy analysis.
License: GPL-3
Imports: vegan (>= 2.5-6), BiodiversityR (>= 2.12-3), adegenet
Depends: R (>= 3.5.0)
Suggests: poppr, mgcv, dplyr, ggplot2, GGally, ggforce, ggrepel, ggsci, gggibbous, gganimate, patchwork
Packaged: 2021-01-23 05:31:52 UTC; RKINDT
NeedsCompilation: no
Repository: CRAN
Date/Publication: 2021-01-26 13:00:02 UTC

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Package proj4 updated to version 1.0-10.1 with previous version 1.0-10 dated 2020-03-02

Title: A simple interface to the PROJ.4 cartographic projections library
Description: A simple interface to lat/long projection and datum transformation of the PROJ.4 cartographic projections library. It allows transformation of geographic coordinates from one projection and/or datum to another.
Author: Simon Urbanek <simon.urbanek@r-project.org>
Maintainer: Simon Urbanek <simon.urbanek@r-project.org>

Diff between proj4 versions 1.0-10 dated 2020-03-02 and 1.0-10.1 dated 2021-01-26

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Package humanleague updated to version 2.1.8 with previous version 2.1.2 dated 2020-02-14

Title: Synthetic Population Generator
Description: Generates high-entropy integer synthetic populations from marginal and (optionally) seed data using quasirandom sampling, in arbitrary dimensionality (Smith, Lovelace and Birkin (2017) <doi:10.18564/jasss.3550>). The package also provides an implementation of the Iterative Proportional Fitting (IPF) algorithm (Zaloznik (2011) <doi:10.13140/2.1.2480.9923>).
Author: Andrew Smith [aut, cre], Steven Johnson [ctb] (Sobol sequence generator implementation), Massachusetts Institute of Technology [cph] (Sobol sequence generator implementation), John Burkhardt [ctb, cph] (C++ implementation of incomplete gamma function), G Bhattacharjee [ctb] (Original FORTRAN implementation of incomplete gamma function)
Maintainer: Andrew Smith <andrew@friarswood.net>

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

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

2015-06-28 0.0.1

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Package bootcluster (with last version 0.2.0) was removed from CRAN

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

2020-10-20 0.2.0
2017-11-13 0.1.0

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Package dynamichazard (with last version 0.6.7) was removed from CRAN

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

2020-12-16 0.6.7
2019-10-14 0.6.6
2019-04-05 0.6.5
2019-03-11 0.6.4
2019-01-11 0.6.3
2019-01-10 0.6.2
2018-10-22 0.6.1
2018-10-09 0.6.0
2018-07-01 0.5.3
2018-06-25 0.5.2
2017-11-25 0.5.1
2017-11-22 0.5.0
2017-09-16 0.4.0
2017-07-15 0.3.5
2017-06-26 0.3.4
2017-06-18 0.3.3
2017-06-09 0.3.2
2017-06-08 0.3.1
2017-06-07 0.3.0
2017-01-20 0.2.0
2016-12-28 0.1.0

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Package kdtools (with last version 0.4.2) was removed from CRAN

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

2020-06-24 0.4.2

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Package neonUtilities updated to version 2.0.0 with previous version 1.3.9 dated 2021-01-12

Title: Utilities for Working with NEON Data
Description: NEON data packages can be accessed through the NEON Data Portal <https://data.neonscience.org/home> or through the NEON Data API (see <https://data.neonscience.org/data-api> for documentation). Data delivered from the Data Portal are provided as monthly zip files packaged within a parent zip file, while individual files can be accessed from the API. This package provides tools that aid in discovering, downloading, and reformatting data prior to use in analyses. This includes downloading data via the API, merging data tables by type, and converting formats. For more information, see the readme file at <https://github.com/NEONScience/NEON-utilities>.
Author: Claire Lunch [aut, cre, ctb], Christine Laney [aut, ctb], Nathan Mietkiewicz [aut, ctb], Eric Sokol [aut, ctb], Kaelin Cawley [aut, ctb], NEON (National Ecological Observatory Network) [aut]
Maintainer: Claire Lunch <clunch@battelleecology.org>

Diff between neonUtilities versions 1.3.9 dated 2021-01-12 and 2.0.0 dated 2021-01-26

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Package MGSDA updated to version 1.5 with previous version 1.4 dated 2016-06-13

Title: Multi-Group Sparse Discriminant Analysis
Description: Implements Multi-Group Sparse Discriminant Analysis proposal of I.Gaynanova, J.Booth and M.Wells (2016), Simultaneous sparse estimation of canonical vectors in the p>>N setting, JASA <doi:10.1080/01621459.2015.1034318>.
Author: Irina Gaynanova
Maintainer: Irina Gaynanova <irinag@stat.tamu.edu>

Diff between MGSDA versions 1.4 dated 2016-06-13 and 1.5 dated 2021-01-26

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Package merDeriv updated to version 0.2-3 with previous version 0.2-2 dated 2020-10-22

Title: Case-Wise and Cluster-Wise Derivatives for Mixed Effects Models
Description: Compute case-wise and cluster-wise derivative for mixed effects models with respect to fixed effects parameter, random effect (co)variances, and residual variance. This material is partially based on work supported by the National Science Foundation under Grant Number 1460719.
Author: Ting Wang [aut, cre], Edgar Merkle [aut] (<https://orcid.org/0000-0001-7158-0653>), Yves Rosseel [ctb]
Maintainer: Ting Wang <twb8d@mail.missouri.edu>

Diff between merDeriv versions 0.2-2 dated 2020-10-22 and 0.2-3 dated 2021-01-26

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Package aqp updated to version 1.27 with previous version 1.25 dated 2020-10-19

Title: Algorithms for Quantitative Pedology
Description: The Algorithms for Quantitative Pedology (AQP) project was started in 2009 to organize a loosely-related set of concepts and source code on the topic of soil profile visualization, aggregation, and classification into this package (aqp). Over the past 8 years, the project has grown into a suite of related R packages that enhance and simplify the quantitative analysis of soil profile data. Central to the AQP project is a new vocabulary of specialized functions and data structures that can accommodate the inherent complexity of soil profile information; freeing the scientist to focus on ideas rather than boilerplate data processing tasks <doi:10.1016/j.cageo.2012.10.020>. These functions and data structures have been extensively tested and documented, applied to projects involving hundreds of thousands of soil profiles, and deeply integrated into widely used tools such as SoilWeb <https://casoilresource.lawr.ucdavis.edu/soilweb-apps/>. Components of the AQP project (aqp, soilDB, sharpshootR, soilReports packages) serve an important role in routine data analysis within the USDA-NRCS Soil Science Division. The AQP suite of R packages offer a convenient platform for bridging the gap between pedometric theory and practice.
Author: Dylan Beaudette [aut, cre], Pierre Roudier [aut, ctb], Andrew Brown [aut, ctb]
Maintainer: Dylan Beaudette <dylan.beaudette@usda.gov>

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Package egor (with last version 0.21.01) was removed from CRAN

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

2021-01-15 0.21.01
2020-06-12 0.20.06
2020-03-02 0.20.03
2020-01-27 0.20.01
2019-10-07 0.19.10

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Package effectFusion (with last version 1.1.2) was removed from CRAN

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

2019-10-24 1.1.2
2019-01-19 1.1.1
2019-01-07 1.1
2016-11-29 1.0

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Package ridge (with last version 2.8) was removed from CRAN

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2021-01-15 2.8
2020-09-04 2.7
2020-09-02 2.6
2020-03-20 2.5
2019-03-15 2.4
2018-07-26 2.3
2017-02-27 2.2

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Package island (with last version 0.2.7) was removed from CRAN

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

2021-01-25 0.2.7
2020-12-07 0.2.6
2020-03-18 0.2.5
2019-04-15 0.2.4
2019-03-21 0.2.3
2019-01-21 0.2.2
2018-05-09 0.2.1
2017-07-10 0.1.3
2016-04-06 0.1.2

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Package diveMove (with last version 1.5.2) was removed from CRAN

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

2020-09-20 1.5.2
2020-09-12 1.5.1
2020-04-29 1.4.6
2019-01-03 1.4.5
2017-12-16 1.4.4
2017-03-06 1.4.3
2017-02-23 1.4.2
2016-02-06 1.4.1
2015-08-23 1.4.0
2014-02-20 1.3.9
2013-06-20 1.3.7
2013-03-28 1.3.6
2012-08-16 1.3.5
2012-05-08 1.3.4
2012-04-05 1.3.3
2012-03-28 1.3.2
2012-03-12 1.3.1
2012-02-06 1.2.9
2011-10-06 1.2.7
2011-05-27 1.2.6
2011-04-04 1.2.5
2011-03-01 1.2.4
2010-11-29 1.2.3
2010-10-07 1.2.2
2010-10-06 1.2.1
2010-09-15 1.2
2010-08-05 1.1
2010-06-13 1.0
2010-06-08 0.9.9
2010-04-25 0.9.8
2010-02-05 0.9.7
2009-10-21 0.9.6
2009-02-15 0.9.5
2008-11-04 0.9.4
2008-10-24 0.9.3
2008-10-23 0.9.2
2008-06-13 0.9.1
2008-01-29 0.9.0
2008-01-28 0.8.9
2008-01-13 0.8.7
2008-01-08 0.8.6
2007-11-09 0.8.4
2007-11-09 0.8.5
2007-10-19 0.8.3
2007-07-13 0.8.2
2007-07-09 0.8.1
2007-07-08 0.8.0
2007-02-17 0.7-8

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Package PNADcIBGE updated to version 0.6.2 with previous version 0.6.1 dated 2020-12-11

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>

Diff between PNADcIBGE versions 0.6.1 dated 2020-12-11 and 0.6.2 dated 2021-01-26

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

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 0.1.0 dated 2020-12-16 and 0.1.1 dated 2021-01-26

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Package clustermole updated to version 1.1.0 with previous version 1.0.1 dated 2020-01-27

Title: Unbiased Single-Cell Transcriptomic Data Cell Type Identification
Description: Assignment of cell type labels to single-cell RNA sequencing (scRNA-seq) clusters is often a time-consuming process that involves manual inspection of the cluster marker genes complemented with a detailed literature search. This is especially challenging when unexpected or poorly described populations are present. The clustermole R package provides methods to query thousands of human and mouse cell identity markers sourced from a variety of databases.
Author: Igor Dolgalev [aut, cre]
Maintainer: Igor Dolgalev <igor.dolgalev@nyumc.org>

Diff between clustermole versions 1.0.1 dated 2020-01-27 and 1.1.0 dated 2021-01-26

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Package spBayesSurv updated to version 1.1.5 with previous version 1.1.4 dated 2020-02-23

Title: Bayesian Modeling and Analysis of Spatially Correlated Survival Data
Description: Provides several Bayesian survival models for spatial/non-spatial survival data: proportional hazards (PH), accelerated failure time (AFT), proportional odds (PO), and accelerated hazards (AH), a super model that includes PH, AFT, PO and AH as special cases, Bayesian nonparametric nonproportional hazards (LDDPM), generalized accelerated failure time (GAFT), and spatially smoothed Polya tree density estimation. The spatial dependence is modeled via frailties under PH, AFT, PO, AH and GAFT, and via copulas under LDDPM and PH. Model choice is carried out via the logarithm of the pseudo marginal likelihood (LPML), the deviance information criterion (DIC), and the Watanabe-Akaike information criterion (WAIC). See Zhou, Hanson and Zhang (2020) <doi:10.18637/jss.v092.i09>.
Author: Haiming Zhou <zhouh@niu.edu> and Timothy Hanson <hansont@stat.sc.edu>
Maintainer: Haiming Zhou <zhouh@niu.edu>

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