Tue, 28 Jan 2020

Package rsparkling updated to version 0.2.19 with previous version 0.2.18 dated 2019-01-30

Title: R Interface for H2O Sparkling Water
Description: An extension package for 'sparklyr' that provides an R interface to H2O Sparkling Water machine learning library (see <https://github.com/h2oai/sparkling-water> for more information).
Author: Jakub Hava [aut, cre], Navdeep Gill [aut], Erin LeDell [aut], Michal Malohlava [aut], JJ Allaire [aut], H2O.ai [cph], RStudio [cph]
Maintainer: Jakub Hava <jakub@h2o.ai>

Diff between rsparkling versions 0.2.18 dated 2019-01-30 and 0.2.19 dated 2020-01-28

 rsparkling-0.2.18/rsparkling/R/h2o_context.R  |only
 rsparkling-0.2.18/rsparkling/R/install_h2o.R  |only
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 rsparkling-0.2.19/rsparkling/NAMESPACE        |   25 ----
 rsparkling-0.2.19/rsparkling/R/package.R      |  155 +-------------------------
 rsparkling-0.2.19/rsparkling/tests/testthat.R |   15 --
 11 files changed, 20 insertions(+), 209 deletions(-)

More information about rsparkling at CRAN
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Package ncf updated to version 1.2-9 with previous version 1.2-8 dated 2019-03-22

Title: Spatial Covariance Functions
Description: Spatial (cross-)covariance and related geostatistical tools: the nonparametric (cross-)covariance function , the spline correlogram, the nonparametric phase coherence function, local indicators of spatial association (LISA), (Mantel) correlogram, (Partial) Mantel test.
Author: Ottar N. Bjornstad [aut, cre], Jun Cai [ctb]
Maintainer: Ottar N. Bjornstad <onb1@psu.edu>

Diff between ncf versions 1.2-8 dated 2019-03-22 and 1.2-9 dated 2020-01-28

 CHANGES                     |    2 +
 DESCRIPTION                 |   12 ++++----
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 R/Sncf.R                    |    8 ++---
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 R/lisa.R                    |    8 ++---
 R/mSynch.R                  |    4 +-
 R/mantel-test.R             |   10 +++----
 R/spline-correlog.R         |    8 ++---
 R/spline-correlog2D.R       |    4 +-
 R/utilities.R               |    4 +-
 man/Sncf.Rd                 |    4 +-
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 man/spline.correlog2D.Rd    |    4 +-
 31 files changed, 122 insertions(+), 120 deletions(-)

More information about ncf at CRAN
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Package boral updated to version 1.8 with previous version 1.7 dated 2018-10-21

Title: Bayesian Ordination and Regression AnaLysis
Description: Bayesian approaches for analyzing multivariate data in ecology. Estimation is performed using Markov Chain Monte Carlo (MCMC) methods via Three. JAGS types of models may be fitted: 1) With explanatory variables only, boral fits independent column Generalized Linear Models (GLMs) to each column of the response matrix; 2) With latent variables only, boral fits a purely latent variable model for model-based unconstrained ordination; 3) With explanatory and latent variables, boral fits correlated column GLMs with latent variables to account for any residual correlation between the columns of the response matrix.
Author: Francis K.C. Hui <fhui28@gmail.com>, with contributions from Wade Blanchard <wade.blanchard@anu.edu.au>
Maintainer: Francis Hui <fhui28@gmail.com>

Diff between boral versions 1.7 dated 2018-10-21 and 1.8 dated 2020-01-28

 DESCRIPTION                    |   14 
 MD5                            |   83 ++--
 NAMESPACE                      |   18 
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More information about boral at CRAN
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Package rel updated to version 1.4.1 with previous version 1.4.0 dated 2020-01-19

Title: Reliability Coefficients
Description: Derives point estimates with confidence intervals for Bennett et als S, Cohen's kappa, Conger's kappa, Fleiss' kappa, Gwet's AC, intraclass correlation coefficients, Krippendorff's alpha, Scott's pi, the standard error of measurement, and weighted kappa.
Author: Riccardo LoMartire
Maintainer: Riccardo LoMartire <lomartire@kth.se>

Diff between rel versions 1.4.0 dated 2020-01-19 and 1.4.1 dated 2020-01-28

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 NEWS        |    4 ++++
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 R/ckap.R    |    4 ++--
 R/gac.R     |    4 ++--
 R/kra.R     |   14 +++++++-------
 R/spi.R     |    4 ++--
 8 files changed, 28 insertions(+), 24 deletions(-)

More information about rel at CRAN
Permanent link

Package tidybayes updated to version 2.0.1 with previous version 1.1.0 dated 2019-06-02

Title: Tidy Data and 'Geoms' for Bayesian Models
Description: Compose data for and extract, manipulate, and visualize posterior draws from Bayesian models ('JAGS', 'Stan', 'rstanarm', 'brms', 'MCMCglmm', 'coda', ...) in a tidy data format. Functions are provided to help extract tidy data frames of draws from Bayesian models and that generate point summaries and intervals in a tidy format. In addition, 'ggplot2' 'geoms' and 'stats' are provided for common visualization primitives like points with multiple uncertainty intervals, eye plots (intervals plus densities), and fit curves with multiple, arbitrary uncertainty bands.
Author: Matthew Kay [aut, cre], Timothy Mastny [ctb]
Maintainer: Matthew Kay <mjskay@umich.edu>

Diff between tidybayes versions 1.1.0 dated 2019-06-02 and 2.0.1 dated 2020-01-28

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 tidybayes-2.0.1/tidybayes/DESCRIPTION                                                                             |   47 
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 tidybayes-2.0.1/tidybayes/NAMESPACE                                                                               |  151 
 tidybayes-2.0.1/tidybayes/NEWS.md                                                                                 |   49 
 tidybayes-2.0.1/tidybayes/R/add_draws.R                                                                           |   51 
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 tidybayes-2.0.1/tidybayes/R/combine_chains.R                                                                      |   22 
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 tidybayes-2.0.1/tidybayes/R/data.R                                                                                |    8 
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 tidybayes-2.0.1/tidybayes/R/fitted_draws.R                                                                        |    7 
 tidybayes-2.0.1/tidybayes/R/gather_draws.R                                                                        |    8 
 tidybayes-2.0.1/tidybayes/R/gather_emmeans_draws.R                                                                |   44 
 tidybayes-2.0.1/tidybayes/R/gather_pairs.R                                                                        |   28 
 tidybayes-2.0.1/tidybayes/R/gather_variables.R                                                                    |   48 
 tidybayes-2.0.1/tidybayes/R/geom.R                                                                                |  123 
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 tidybayes-2.0.1/tidybayes/R/geom_eye.R                                                                            |  155 
 tidybayes-2.0.1/tidybayes/R/geom_interval.R                                                                       |  163 
 tidybayes-2.0.1/tidybayes/R/geom_intervalh.R                                                                      |  102 
 tidybayes-2.0.1/tidybayes/R/geom_lineribbon.R                                                                     |   74 
 tidybayes-2.0.1/tidybayes/R/geom_pointinterval.R                                                                  |  187 
 tidybayes-2.0.1/tidybayes/R/geom_pointintervalh.R                                                                 |  103 
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 tidybayes-2.0.1/tidybayes/R/predicted_draws.R                                                                     |  113 
 tidybayes-2.0.1/tidybayes/R/recover_types.R                                                                       |   42 
 tidybayes-2.0.1/tidybayes/R/sample_draws.R                                                                        |    6 
 tidybayes-2.0.1/tidybayes/R/scales.R                                                                              |only
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 tidybayes-2.0.1/tidybayes/R/stat.R                                                                                |   36 
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 tidybayes-2.0.1/tidybayes/R/stat_pointinterval.R                                                                  |  145 
 tidybayes-2.0.1/tidybayes/R/stat_pointintervalh.R                                                                 |   76 
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 tidybayes-2.0.1/tidybayes/R/theme_tidybayes.R                                                                     |    5 
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 tidybayes-2.0.1/tidybayes/R/tidy_format_translators.R                                                             |   26 
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 tidybayes-2.0.1/tidybayes/R/unspread_draws.R                                                                      |   24 
 tidybayes-2.0.1/tidybayes/R/util.R                                                                                |   23 
 tidybayes-2.0.1/tidybayes/R/x_at_y.R                                                                              |   25 
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 tidybayes-2.0.1/tidybayes/inst/doc/tidy-rstanarm.R                                                                |  103 
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 tidybayes-2.0.1/tidybayes/inst/doc/tidybayes-residuals.R                                                          |  123 
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 tidybayes-2.0.1/tidybayes/inst/doc/tidybayes.html                                                                 | 2075 ++++------
 tidybayes-2.0.1/tidybayes/man/RankCorr.Rd                                                                         |   56 
 tidybayes-2.0.1/tidybayes/man/add_draws.Rd                                                                        |  154 
 tidybayes-2.0.1/tidybayes/man/add_predicted_draws.Rd                                                              |  541 +-
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 tidybayes-2.0.1/tidybayes/man/tidybayes-ggproto.Rd                                                                |   40 
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 tidybayes-2.0.1/tidybayes/man/unspread_draws.Rd                                                                   |  159 
 tidybayes-2.0.1/tidybayes/man/x_at_y.Rd                                                                           |   96 
 tidybayes-2.0.1/tidybayes/tests/figs/deps.txt                                                                     |    2 
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Package oro.nifti updated to version 0.10.1 with previous version 0.9.1 dated 2017-10-26

Title: Rigorous - 'NIfTI' + 'ANALYZE' + 'AFNI' : Input / Output
Description: Functions for the input/output and visualization of medical imaging data that follow either the 'ANALYZE', 'NIfTI' or 'AFNI' formats. This package is part of the Rigorous Analytics bundle.
Author: Brandon Whitcher [aut, cre], Volker Schmid [aut], Andrew Thornton [aut], Karsten Tabelow [ctb], Jon Clayden [ctb], John Muschelli [aut]
Maintainer: Brandon Whitcher <bwhitcher@gmail.com>

Diff between oro.nifti versions 0.9.1 dated 2017-10-26 and 0.10.1 dated 2020-01-28

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 oro.nifti-0.10.1/oro.nifti/R/anlz_Operators.R               |    2 
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Package httptest updated to version 3.3.0 with previous version 3.2.2 dated 2018-12-07

Title: A Test Environment for HTTP Requests
Description: Testing and documenting code that communicates with remote servers can be painful. Dealing with authentication, server state, and other complications can make testing seem too costly to bother with. But it doesn't need to be that hard. This package enables one to test all of the logic on the R sides of the API in your package without requiring access to the remote service. Importantly, it provides three contexts that mock the network connection in different ways, as well as testing functions to assert that HTTP requests were---or were not---made. It also allows one to safely record real API responses to use as test fixtures. The ability to save responses and load them offline also enables one to write vignettes and other dynamic documents that can be distributed without access to a live server.
Author: Neal Richardson [aut, cre]
Maintainer: Neal Richardson <neal.p.richardson@gmail.com>

Diff between httptest versions 3.2.2 dated 2018-12-07 and 3.3.0 dated 2020-01-28

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Package gglogo updated to version 0.1.5 with previous version 0.1.4 dated 2019-06-28

Title: Geom for Logo Sequence Plots
Description: Visualize sequences in (modified) logo plots. The design choices used by these logo plots allow sequencing data to be more easily analyzed. Because it is integrated into the 'ggplot2' geom framework, these logo plots support native features such as faceting.
Author: Heike Hofmann [aut], Eric Hare [aut, cre], GGobi Foundation [aut]
Maintainer: Eric Hare <eric@oaiti.org>

Diff between gglogo versions 0.1.4 dated 2019-06-28 and 0.1.5 dated 2020-01-28

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Package ShinyItemAnalysis updated to version 1.3.2 with previous version 1.3.1 dated 2019-06-26

Title: Test and Item Analysis via Shiny
Description: Interactive shiny application for analysis of educational tests and their items.
Author: Patricia Martinkova [aut, cre], Adela Hladka [aut], Ondrej Leder [ctb], Jakub Houdek [ctb], Lubomir Stepanek [ctb], Tomas Jurica [ctb], Jana Vorlickova [ctb], Jan Netik [ctb]
Maintainer: Patricia Martinkova <martinkova@cs.cas.cz>

Diff between ShinyItemAnalysis versions 1.3.1 dated 2019-06-26 and 1.3.2 dated 2020-01-28

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 R/HCIkey.R                                                         |    8 
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New package soilDB with initial version 2.5
Package: soilDB
Type: Package
Title: Soil Database Interface
Version: 2.5
Date: 2020-01-27
Authors@R: c(person(given="Dylan", family="Beaudette", role = c("cre", "aut"), email = "dylan.beaudette@usda.gov"), person(given="Jay", family="Skovlin", role = c("aut")), person(given="Stephen", family="Roecker", role = c("aut")) )
Author: Dylan Beaudette [cre, aut], Jay Skovlin [aut], Stephen Roecker [aut]
Maintainer: Dylan Beaudette <dylan.beaudette@usda.gov>
Description: A collection of functions for reading data from USDA-NCSS soil databases.
License: GPL (>= 3)
LazyLoad: yes
Depends: R (>= 3.0.0)
Imports: aqp, grDevices, graphics, stats, utils, plyr, xml2, sp, reshape2, raster, curl, lattice
Suggests: rgdal, jsonlite, RODBC, httr, rgeos, rvest, testthat, stringr, latticeExtra, RCurl, XML, ggplot2, gridExtra, viridis
Repository: CRAN
URL: http://ncss-tech.github.io/AQP/
BugReports: https://github.com/ncss-tech/soilDB/issues
RoxygenNote: 7.0.2
NeedsCompilation: no
Packaged: 2020-01-27 19:50:39 UTC; Dylan.Beaudette
Date/Publication: 2020-01-28 20:40:02 UTC

More information about soilDB at CRAN
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Package rmapshaper updated to version 0.4.3 with previous version 0.4.2 dated 2020-01-17

Title: Client for 'mapshaper' for 'Geospatial' Operations
Description: Edit and simplify 'geojson', 'Spatial', and 'sf' objects. This is wrapper around the 'mapshaper' 'JavaScript' library by Matthew Bloch <https://github.com/mbloch/mapshaper/> to perform topologically-aware polygon simplification, as well as other operations such as clipping, erasing, dissolving, and converting 'multi-part' to 'single-part' geometries. It relies on the 'geojsonio' package for working with 'geojson' objects, the 'sf' package for working with 'sf' objects, and the 'sp' and 'rgdal' packages for working with 'Spatial' objects.
Author: Andy Teucher [aut, cre], Kenton Russell [aut] (JavaScript support), Matthew Bloch [cph] (mapshaper Javascript library)
Maintainer: Andy Teucher <andy.teucher@gmail.com>

Diff between rmapshaper versions 0.4.2 dated 2020-01-17 and 0.4.3 dated 2020-01-28

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Package rlang updated to version 0.4.4 with previous version 0.4.3 dated 2020-01-24

Title: Functions for Base Types and Core R and 'Tidyverse' Features
Description: A toolbox for working with base types, core R features like the condition system, and core 'Tidyverse' features like tidy evaluation.
Author: Lionel Henry [aut, cre], Hadley Wickham [aut], RStudio [cph]
Maintainer: Lionel Henry <lionel@rstudio.com>

Diff between rlang versions 0.4.3 dated 2020-01-24 and 0.4.4 dated 2020-01-28

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New package FPDclustering with initial version 1.4.1
Package: FPDclustering
Type: Package
Title: PD-Clustering and Factor PD-Clustering
Version: 1.4.1
Date: 2020-01-28
Author: Cristina Tortora [aut, cre, cph], Noe Vidales [aut], Francesco Palumbo [aut], and Paul D. McNicholas [fnd]
Maintainer: Cristina Tortora <grikris1@gmail.com>
Description: Probabilistic distance clustering (PD-clustering) is an iterative, distribution free, probabilistic clustering method. PD-clustering assigns units to a cluster according to their probability of membership, under the constraint that the product of the probability and the distance of each point to any cluster centre is a constant. PD-clustering is a flexible method that can be used with non-spherical clusters, outliers, or noisy data. PDQ is an extension of the algorithm for clusters of different size. GPDC and TPDC uses a dissimilarity measure based on densities. Factor PD-clustering (FPDC) is a recently proposed factor clustering method that involves a linear transformation of variables and a cluster optimizing the PD-clustering criterion. It works on high dimensional datasets.
Depends: ThreeWay ,mvtnorm,R (>= 3.5)
Imports: ExPosition,cluster,rootSolve
License: GPL (>= 2)
NeedsCompilation: no
Packaged: 2020-01-28 18:15:17 UTC; cristina
Repository: CRAN
Date/Publication: 2020-01-28 20:50:05 UTC

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Package fillr updated to version 1.0.0 with previous version 0.1.1 dated 2019-08-02

Title: Fill Missing Values in Vectors
Description: Edit vectors to fill missing values, based on the vector itself.
Author: Jelger van Zaane [aut, cre]
Maintainer: Jelger van Zaane <me@jelgervanzaane.nl>

Diff between fillr versions 0.1.1 dated 2019-08-02 and 1.0.0 dated 2020-01-28

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Package GeNetIt updated to version 0.1-3 with previous version 0.1-2 dated 2019-10-03

Title: Spatial Graph-Theoretic Genetic Gravity Modelling
Description: Implementation of spatial graph-theoretic genetic gravity models. The model framework is applicable for other types of spatial flow questions. Includes functions for constructing spatial graphs, sampling and summarizing associated raster variables and building unconstrained and singly constrained gravity models.
Author: Jeffrey S. Evans [aut, cre], Melanie Murphy [aut]
Maintainer: Jeffrey S. Evans <jeffrey_evans@tnc.org>

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Package corto updated to version 1.0.1 with previous version 0.99.10 dated 2019-10-30

Title: Inference of Gene Regulatory Networks
Description: We present 'corto' (Correlation Tool), a simple package to infer gene regulatory networks and visualize master regulators from gene expression data using DPI (Data Processing Inequality) and bootstrapping to recover edges. An initial step is performed to calculate all significant edges between a list of source nodes (centroids) and target genes. Then all triplets containing two centroids and one target are tested in a DPI step which removes edges. A bootstrapping process then calculates the robustness of the network, eventually re-adding edges previously removed by DPI. The package implements a similar pipeline as ARACNe-AP (Algorithm for the Reconstruction of Accurate Cellular Networks with Adaptive Partitioning) by Giorgi (2016) <doi:10.1093/bioinformatics/btw216>) with optimizations to run outside a computing cluster (most notably correlation to infer feature dependencies instead of Mutual Information).
Author: Federico M. Giorgi [aut, cre], Daniele Mercatelli [ctb], Gonzalo Lopez-Garcia [ctb]
Maintainer: Federico M. Giorgi <federico.giorgi@gmail.com>

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Package mimsy updated to version 0.4.3 with previous version 0.4.2 dated 2019-03-10

Title: Calculate MIMS Dissolved Gas Concentrations Without Getting a Headache
Description: Calculate dissolved gas concentrations from raw MIMS (Membrane Inlet Mass Spectrometer) signal data. Use mimsy() on a formatted CSV file to return dissolved gas concentrations (mg and microMole) of N2, O2, Ar based on gas solubility at temperature, pressure, and salinity. See references Benson and Krause (1984) <DOI:10.4319/lo.1992.37.6.1307>, Garcia and Gordon (1992) <DOI:10.4319/lo.1984.29.3.0620>, Stull (1947) <DOI:10.1021/ie50448a022>, and Hamme and Emerson (2004) <DOI:10.1016/j.dsr.2004.06.009> for more information. Easily save the output to a nicely-formatted multi-tab 'Excel' workbook with mimsy.save(). Supports dual-temperature standard calibration for dual-bath MIMS setups.
Author: Michelle C. Kelly [aut, cre]
Maintainer: Michelle C. Kelly <michellecatherinekelly@gmail.com>

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Package rowr (with last version 1.1.3) was removed from CRAN

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

2016-12-21 1.1.3
2015-04-30 1.1.2
2014-11-26 1.1.1
2014-08-15 1.0.1
2014-07-23 1.0

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Package lingtypology (with last version 1.0.15) was removed from CRAN

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2019-08-26 1.0.14
2018-06-14 1.0.13
2018-03-10 1.0.12
2018-01-14 1.0.11
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2017-08-16 1.0.6
2017-06-21 1.0.5
2017-05-13 1.0.4
2017-04-16 1.0.3
2017-02-23 1.0.2
2017-01-29 1.0.1
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Package pcaL1 (with last version 1.5.3) was removed from CRAN

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2017-04-10 1.5.1
2017-03-12 1.5
2016-12-20 1.4.1
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2015-04-25 1.3
2013-12-23 1.2.1
2012-07-06 1.2
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Package TPMplt (with last version 0.1.3) was removed from CRAN

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2018-12-14 0.1.2
2018-12-02 0.1.1
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Package iemisc (with last version 0.9.7) was removed from CRAN

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2016-07-14 0.9.1
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Package AutoModel (with last version 0.4.9) was removed from CRAN

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2015-08-23 0.4.9

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Package listless (with last version 0.0-2) was removed from CRAN

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2016-08-12 0.0-2

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Package RtextSummary (with last version 0.1.0) was removed from CRAN

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2019-06-07 0.1.0

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Package econetwork (with last version 0.2) was removed from CRAN

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2019-07-08 0.2
2019-01-11 0.1

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Package Matrix.utils (with last version 0.9.7) was removed from CRAN

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2018-04-19 0.9.7
2017-08-28 0.9.6
2016-12-21 0.9.5
2016-12-14 0.9.4
2016-09-22 0.9.3
2016-07-15 0.9.2
2016-06-16 0.9.1
2016-03-28 0.9.0
2015-12-15 0.5

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Package rqPen updated to version 2.2.1 with previous version 2.2 dated 2019-12-10

Title: Penalized Quantile Regression
Description: Performs penalized quantile regression for LASSO, SCAD and MCP functions including group penalties. Provides a function that automatically generates lambdas and evaluates different models with cross validation or BIC, including a large p version of BIC.
Author: Ben Sherwood [aut, cre], Adam Maidman [ctb]
Maintainer: Ben Sherwood <ben.sherwood@ku.edu>

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Package rorcid updated to version 0.6.0 with previous version 0.5.0 dated 2019-06-07

Title: Interface to the 'Orcid.org' API
Description: Client for the 'Orcid.org' API (<https://orcid.org/>). Functions included for searching for people, searching by 'DOI', and searching by 'Orcid' 'ID'.
Author: Scott Chamberlain [aut, cre] (<https://orcid.org/0000-0003-1444-9135>), rOpenSci [fnd] (https://ropensci.org/)
Maintainer: Scott Chamberlain <myrmecocystus@gmail.com>

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Package doRedis updated to version 2.0.0 with previous version 1.1.1 dated 2014-04-03

Title: 'Foreach' Parallel Adapter Using the 'Redis' Database
Description: A parallel back end for the 'foreach' package using the 'Redis' database.
Author: B. W. Lewis <blewis@illposed.net>
Maintainer: B. W. Lewis <blewis@illposed.net>

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Package updog updated to version 1.2.0 with previous version 1.1.3 dated 2019-11-21

Title: Flexible Genotyping for Polyploids
Description: Implements empirical Bayes approaches to genotype polyploids from next generation sequencing data while accounting for allelic bias, overdispersion, and sequencing error. The main functions are flexdog() and multidog(), which allow the specification of many different genotype distributions. An experimental function that takes into account varying levels of relatedness is implemented in mupdog(). Also provided are functions to simulate genotypes, rgeno(), and read-counts, rflexdog(), as well as functions to calculate oracle genotyping error rates, oracle_mis(), and correlation with the true genotypes, oracle_cor(). These latter two functions are useful for read depth calculations. Run browseVignettes(package = "updog") in R for example usage. See Gerard et al. (2018) <doi:10.1534/genetics.118.301468> and Gerard and Ferrao (2019) <doi:10.1093/bioinformatics/btz852> for details on the implemented methods.
Author: David Gerard [aut, cre] (<https://orcid.org/0000-0001-9450-5023>)
Maintainer: David Gerard <gerard.1787@gmail.com>

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Package tokenbrowser updated to version 0.1.2 with previous version 0.1.1 dated 2019-10-24

Title: Create Full Text Browsers from Annotated Token Lists
Description: Create browsers for reading full texts from a token list format. Information obtained from text analyses (e.g., topic modeling, word scaling) can be used to annotate the texts.
Author: Kasper Welbers and Wouter van Atteveldt
Maintainer: Kasper Welbers <kasperwelbers@gmail.com>

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Package Quartet updated to version 1.1.0 with previous version 1.0.3 dated 2019-12-30

Title: Comparison of Phylogenetic Trees Using Quartet and Split Measures
Description: Calculates the number of four-taxon subtrees consistent with a pair of cladograms, calculating the symmetric quartet distance of Bandelt & Dress (1986), Reconstructing the shape of a tree from observed dissimilarity data, Advances in Applied Mathematics, 7, 309-343 <doi:10.1016/0196-8858(86)90038-2>, and using the tqDist algorithm of Sand et al. (2014), tqDist: a library for computing the quartet and triplet distances between binary or general trees, Bioinformatics, 30, 2079–2080 <doi:10.1093/bioinformatics/btu157> for pairs of binary trees.
Author: Martin R. Smith [aut, cre, cph] (<https://orcid.org/0000-0001-5660-1727>), Andreas Sand [ant], Gerth Stølting Brodal [ant], Rolf Fagerberg [ant], Thomas Mailund [ant], Christian N. S. Pedersen [ant], Jens Johansen [ant], Morten K. Holt [ant]
Maintainer: Martin R. Smith <martin.smith@durham.ac.uk>

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Package ragt2ridges updated to version 0.3.4 with previous version 0.3.3 dated 2019-12-05

Title: Ridge Estimation of Vector Auto-Regressive (VAR) Processes
Description: The ragt2ridges-package provides ridge maximum likelihood estimation of vector auto-regressive processes: the VAR(1), VAR(2) and VARX(1) model (more to be added). Prior knowledge may be incorporated in the estimation through a) specification of the edges believed to be absent in the time series chain graph, and b) a shrinkage target towards which the parameter estimate is shrunken for large penalty parameter values. Estimation functionality is accompanied by methodology for penalty parameter selection. In addition, the package offers supporting functionality for the exploitation of estimated models. Among others, i) a procedure to infer the support of the non-sparse ridge estimate (and thereby of the time series chain graph) is implemented, ii) a table of node-wise network summary statistics, iii) mutual information analysis, and iv) impulse response analysis. Cf. Miok et al. (2017) <DOI:10.1002/bimj.201500269> and Miok et al. (2019) <DOI:10.1002/bimj.201700195> for details on the implemented methods.
Author: Wessel N. van Wieringen <w.vanwieringen@vumc.nl>
Maintainer: Wessel N. van Wieringen <w.vanwieringen@vumc.nl>

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Package TropFishR updated to version 1.6.2 with previous version 1.6.1 dated 2019-01-17

Title: Tropical Fisheries Analysis
Description: A compilation of fish stock assessment methods for the analysis of length-frequency data in the context of data-poor fisheries. Includes methods and examples included in the FAO Manual by P. Sparre and S.C. Venema (1998), "Introduction to tropical fish stock assessment" (<http://www.fao.org/documents/card/en/c/9bb12a06-2f05-5dcb-a6ca-2d6dd3080f65/>), as well as other more recent methods.
Author: Tobias K. Mildenberger, Marc H. Taylor, Matthias Wolff
Maintainer: Tobias K. Mildenberger <t.k.mildenberger@gmail.com>

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Package rankFD updated to version 0.0.5 with previous version 0.0.4 dated 2020-01-27

Title: Rank-Based Tests for General Factorial Designs
Description: The rankFD() function calculates the Wald-type statistic (WTS) and the ANOVA-type statistic (ATS) for nonparametric factorial designs, e.g., for count, ordinal or score data in a crossed design with an arbitrary number of factors.
Author: Frank Konietschke, Sarah Friedrich, Edgar Brunner, Markus Pauly
Maintainer: Frank Konietschke <frank.konietschke@charite.de>

Diff between rankFD versions 0.0.4 dated 2020-01-27 and 0.0.5 dated 2020-01-28

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Package psychotools updated to version 0.5-1 with previous version 0.5-0 dated 2018-12-19

Title: Psychometric Modeling Infrastructure
Description: Infrastructure for psychometric modeling such as data classes (for item response data and paired comparisons), basic model fitting functions (for Bradley-Terry, Rasch, parametric logistic IRT, generalized partial credit, rating scale, multinomial processing tree models), extractor functions for different types of parameters (item, person, threshold, discrimination, guessing, upper asymptotes), unified inference and visualizations, and various datasets for illustration. Intended as a common lightweight and efficient toolbox for psychometric modeling and a common building block for fitting psychometric mixture models in package "psychomix" and trees based on psychometric models in package "psychotree".
Author: Achim Zeileis [aut, cre] (<https://orcid.org/0000-0003-0918-3766>), Carolin Strobl [aut], Florian Wickelmaier [aut], Basil Komboz [aut], Julia Kopf [aut], Lennart Schneider [aut], Rudolf Debelak [aut]
Maintainer: Achim Zeileis <Achim.Zeileis@R-project.org>

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Package phenopix updated to version 2.4 with previous version 2.3.1 dated 2017-06-16

Title: Process Digital Images of a Vegetation Cover
Description: A collection of functions to process digital images, depict greenness index trajectories and extract relevant phenological stages.
Author: Gianluca Filippa, Edoardo Cremonese, Mirco Migliavacca, Marta Galvagno, Matthias Folker, Andrew D. Richardson, Enrico Tomelleri
Maintainer: Gianluca Filippa <gian.filippa@gmail.com>

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New package HURDAT with initial version 0.2.3.1
Package: HURDAT
Type: Package
Title: Hurricane Re-Analysis Project
Version: 0.2.3.1
Authors@R: c( person("Tim", "Trice", email = "tim.trice@gmail.com", role = c("aut", "cre")), person("Chris", "Landsea", email = "Chris.Landsea@noaa.gov", role = c("aut", "dtc")))
Depends: R (>= 3.5)
Description: Scraped dataset of the Hurricane Research Division's Hurricane Re-Analysis Project known as HURDAT. Storm details are available for most known hurricanes and tropical storms for the Atlantic and northeastern Pacific ocean (northwestern hemisphere). See <http://www.aoml.noaa.gov/hrd/hurdat/Data_Storm.html> for more information.
URL: https://github.com/timtrice/HURDAT
BugReports: https://github.com/timtrice/HURDAT/issues
License: MIT + file LICENSE
Language: en-us
LazyData: TRUE
Imports: dplyr, purrr, readr, rlang, rvest, tidyr, xml2
Suggests: covr, devtools, knitr, testthat, rmarkdown
VignetteBuilder: knitr
RoxygenNote: 6.1.1
Encoding: UTF-8
NeedsCompilation: no
Packaged: 2020-01-21 14:17:45 UTC; rstudio-user
Author: Tim Trice [aut, cre], Chris Landsea [aut, dtc]
Maintainer: Tim Trice <tim.trice@gmail.com>
Repository: CRAN
Date/Publication: 2020-01-28 14:20:11 UTC

More information about HURDAT at CRAN
Permanent link

Package ggeffects updated to version 0.14.1 with previous version 0.14.0 dated 2019-12-16

Title: Create Tidy Data Frames of Marginal Effects for 'ggplot' from Model Outputs
Description: Compute marginal effects from statistical models and returns the result as tidy data frames. These data frames are ready to use with the 'ggplot2'-package. Marginal effects can be calculated for many different models. Interaction terms, splines and polynomial terms are also supported. The main functions are ggpredict(), ggemmeans() and ggeffect(). There is a generic plot()-method to plot the results using 'ggplot2'.
Author: Daniel Lüdecke [aut, cre] (<https://orcid.org/0000-0002-8895-3206>), Frederik Aust [ctb] (<https://orcid.org/0000-0003-4900-788X>)
Maintainer: Daniel Lüdecke <d.luedecke@uke.de>

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Package ocedata updated to version 0.1.6 with previous version 0.1.5 dated 2018-12-19

Title: Oceanographic Data Sets for 'oce' Package
Description: Several Oceanographic data sets are provided for use by the 'oce' package and for other purposes.
Author: Dan Kelley [aut, cre] (<https://orcid.org/0000-0001-7808-5911>)
Maintainer: Dan Kelley <Dan.Kelley@Dal.Ca>

Diff between ocedata versions 0.1.5 dated 2018-12-19 and 0.1.6 dated 2020-01-28

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Package nomogramFormula updated to version 1.2.0.0 with previous version 1.1.0.0 dated 2019-09-02

Title: Calculate Total Points and Probabilities for Nomogram
Description: A nomogram, which can be carried out in 'rms' package, provides a graphical explanation of a prediction process. However, it is not very easy to draw straight lines, read points and probabilities accurately. Even, it is hard for users to calculate total points and probabilities for all subjects. This package provides formula_rd() and formula_lp() functions to fit the formula of total points with raw data and linear predictors respectively by polynomial regression. Function points_cal() will help you calculate the total points. prob_cal() can be used to calculate the probabilities after lrm(), cph() or psm() regression. For more complex condition, interaction or restricted cubic spine, TotalPoints.rms() can be used.
Author: Jing Zhang, Zhi Jin
Maintainer: Jing Zhang<zj391120@163.com>

Diff between nomogramFormula versions 1.1.0.0 dated 2019-09-02 and 1.2.0.0 dated 2020-01-28

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New package iNEXT with initial version 2.0.20
Package: iNEXT
Type: Package
Title: Interpolation and Extrapolation for Species Diversity
Version: 2.0.20
Author: T. C. Hsieh, K. H. Ma and Anne Chao
Description: Provides simple functions to compute and plot two types (sample-size- and coverage-based) rarefaction and extrapolation of species diversity (Hill numbers) for individual-based (abundance) data or sampling-unit- based (incidence) data. (Hsieh, Ma and Chao 2014) <doi: 10.1111/2041-210X.12613>.
License: GPL (>= 3)
URL: http://chao.stat.nthu.edu.tw/wordpress/software_download/
Maintainer: T. C. Hsieh <euler96@gmail.com>
Depends: R (>= 3.4)
Imports: stats, graphics, ggplot2, reshape2
BugReports: https://github.com/JohnsonHsieh/iNEXT/issues
LazyLoad: yes
RoxygenNote: 6.1.1
Suggests: testthat, knitr, rmarkdown, gridExtra, ggthemes
VignetteBuilder: knitr
ByteCompile: true
NeedsCompilation: no
Packaged: 2020-01-28 12:36:16 UTC; johnson
Repository: CRAN
Date/Publication: 2020-01-28 13:10:04 UTC

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Package sjlabelled updated to version 1.1.3 with previous version 1.1.2 dated 2020-01-17

Title: Labelled Data Utility Functions
Description: Collection of functions dealing with labelled data, like reading and writing data between R and other statistical software packages like 'SPSS', 'SAS' or 'Stata', and working with labelled data. This includes easy ways to get, set or change value and variable label attributes, to convert labelled vectors into factors or numeric (and vice versa), or to deal with multiple declared missing values.
Author: Daniel Lüdecke [aut, cre] (<https://orcid.org/0000-0002-8895-3206>), David Ranzolin [ctb]
Maintainer: Daniel Lüdecke <d.luedecke@uke.de>

Diff between sjlabelled versions 1.1.2 dated 2020-01-17 and 1.1.3 dated 2020-01-28

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New package SDEFSR with initial version 0.7.21
Package: SDEFSR
Type: Package
Title: Subgroup Discovery with Evolutionary Fuzzy Systems
Version: 0.7.21
Date: 2020-01-28
Authors@R: c(person("Angel M.", "Garcia", email = "agvico@ujaen.es", role = c("aut", "cre")), person("Pedro", "Gonzalez", email = "pglez@ujaen.es", role = c("aut", "cph")), person("Cristobal J.", "Carmona", email = "ccarmona@ujaen.es", role = c("aut", "cph")), person("Francisco", "Charte", email = "francisco@fcharte.com", role = "ctb"), person("Maria J.", "del Jesus", email = "mjjesus@ujaen.es", role = c("aut", "cph")) )
Maintainer: Angel M. Garcia <agvico@ujaen.es>
Description: Implementation of evolutionary fuzzy systems for the data mining task called "subgroup discovery". In particular, the algorithms presented in this package are: M. J. del Jesus, P. Gonzalez, F. Herrera, M. Mesonero (2007) <doi:10.1109/TFUZZ.2006.890662> M. J. del Jesus, P. Gonzalez, F. Herrera (2007) <doi:10.1109/MCDM.2007.369416> C. J. Carmona, P. Gonzalez, M. J. del Jesus, F. Herrera (2010) <doi:10.1109/TFUZZ.2010.2060200> C. J. Carmona, V. Ruiz-Rodado, M. J. del Jesus, A. Weber, M. Grootveld, P. González, D. Elizondo (2015) <doi:10.1016/j.ins.2014.11.030> It also provide a Shiny App to ease the analysis. The algorithms work with data sets provided in KEEL, ARFF and CSV format and also with data.frame objects.
URL: https://github.com/aklxao2/SDR
Depends: R (>= 3.0.0)
License: LGPL (>= 3)
LazyData: TRUE
Imports: grDevices, methods, parallel, stats, utils
Suggests: ggplot2, knitr, shiny (>= 0.11)
VignetteBuilder: knitr
RoxygenNote: 6.1.1
NeedsCompilation: no
Author: Angel M. Garcia [aut, cre], Pedro Gonzalez [aut, cph], Cristobal J. Carmona [aut, cph], Francisco Charte [ctb], Maria J. del Jesus [aut, cph]
Packaged: 2020-01-28 11:51:26 UTC; agvico
Encoding: UTF-8
Repository: CRAN
Date/Publication: 2020-01-28 12:40:10 UTC

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Package repr updated to version 1.1.0 with previous version 1.0.2 dated 2019-12-16

Title: Serializable Representations
Description: String and binary representations of objects for several formats / mime types.
Author: Philipp Angerer [aut, cre] (<https://orcid.org/0000-0002-0369-2888>), Thomas Kluyver [aut], Jan Schulz [aut], abielr [ctb], Denilson Figueiredo de Sa [ctb], Jim Hester [ctb], karldw [ctb], Dave Foster [ctb], Carson Sievert [ctb]
Maintainer: Philipp Angerer <phil.angerer@gmail.com>

Diff between repr versions 1.0.2 dated 2019-12-16 and 1.1.0 dated 2020-01-28

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Package bigutilsr updated to version 0.3.0 with previous version 0.2.2 dated 2019-11-04

Title: Utility Functions for Large-scale Data
Description: Utility functions for large-scale data. For now, package 'bigutilsr' mainly includes functions for outlier detection and PCA projection.
Author: Florian Privé [aut, cre]
Maintainer: Florian Privé <florian.prive.21@gmail.com>

Diff between bigutilsr versions 0.2.2 dated 2019-11-04 and 0.3.0 dated 2020-01-28

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Package staRdom updated to version 1.1.3 with previous version 1.1.1 dated 2019-11-27

Title: PARAFAC Analysis of EEMs from DOM
Description: This is a user-friendly way to run a parallel factor (PARAFAC) analysis (Harshman, 1971) <doi:10.1121/1.1977523> on excitation emission matrix (EEM) data from dissolved organic matter (DOM) samples (Murphy et al., 2013) <doi:10.1039/c3ay41160e>. The analysis includes profound methods for model validation. Some additional functions allow the calculation of absorbance slope parameters and create beautiful plots.
Author: Matthias Pucher [aut, cre], Daniel Graeber [aut, ctb], Stefan Preiner [ctb], Renata Pinto [ctb]
Maintainer: Matthias Pucher <matthias.pucher@wcl.ac.at>

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Package sf updated to version 0.8-1 with previous version 0.8-0 dated 2019-09-17

Title: Simple Features for R
Description: Support for simple features, a standardized way to encode spatial vector data. Binds to 'GDAL' for reading and writing data, to 'GEOS' for geometrical operations, and to 'PROJ' for projection conversions and datum transformations.
Author: Edzer Pebesma [aut, cre] (<https://orcid.org/0000-0001-8049-7069>), Roger Bivand [ctb] (<https://orcid.org/0000-0003-2392-6140>), Etienne Racine [ctb], Michael Sumner [ctb], Ian Cook [ctb], Tim Keitt [ctb], Robin Lovelace [ctb], Hadley Wickham [ctb], Jeroen Ooms [ctb] (<https://orcid.org/0000-0002-4035-0289>), Kirill M<U+00FC>ller [ctb], Thomas Lin Pedersen [ctb], Dan Baston [ctb]
Maintainer: Edzer Pebesma <edzer.pebesma@uni-muenster.de>

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More information about sf at CRAN
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Package difNLR updated to version 1.3.2 with previous version 1.3.1 dated 2020-01-27

Title: DIF and DDF Detection by Non-Linear Regression Models
Description: Detection of differential item functioning (DIF) among dichotomously scored items and differential distractor functioning (DDF) among unscored items with non-linear regression procedures based on generalized logistic regression models (Drabinova and Martinkova, 2017, doi:10.1111/jedm.12158).
Author: Adela Hladka [aut, cre], Patricia Martinkova [aut], Karel Zvara [ctb]
Maintainer: Adela Hladka <hladka@cs.cas.cz>

Diff between difNLR versions 1.3.1 dated 2020-01-27 and 1.3.2 dated 2020-01-28

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Package bikm1 updated to version 1.0.0 with previous version 0.9.0 dated 2019-08-24

Title: Co-Clustering Adjusted Rand Index and Bikm1 Procedure for Contingency and Binary Data-Sets
Description: Co-clustering of the rows and columns of a contingency or binary matrix, or double binary matrices and model selection for the number of row and column clusters. Three models are considered: the Poisson latent block model for contingency matrix, the binary latent block model for binary matrix and a new model we develop: the multiple latent block model for double binary matrices. A new procedure named bikm1 is implemented to investigate more efficiently the grid of numbers of clusters. Then, the studied model selection criteria are the integrated completed likelihood (ICL) and the Bayesian integrated likelihood (BIC). Finally, the co-clustering adjusted Rand index (CARI) to measure agreement between co-clustering partitions is implemented. Robert Valerie and Vasseur Yann (2017) <arXiv:1705.06760>.
Author: Valerie Robert [aut, cre]
Maintainer: Valerie Robert <valerie.robert.math@gmail.com>

Diff between bikm1 versions 0.9.0 dated 2019-08-24 and 1.0.0 dated 2020-01-28

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Package bigassertr updated to version 0.1.2 with previous version 0.1.1 dated 2019-10-14

Title: Assertion and Message Functions
Description: Enhanced message functions (cat() / message() / warning() / error()) using wrappers around sprintf(). Also, multiple assertion functions (e.g. to check class, length, values, files, arguments, etc.).
Author: Florian Privé [aut, cre]
Maintainer: Florian Privé <florian.prive.21@gmail.com>

Diff between bigassertr versions 0.1.1 dated 2019-10-14 and 0.1.2 dated 2020-01-28

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Package rmumps updated to version 5.2.1-10 with previous version 5.2.1-7 dated 2019-12-06

Title: Wrapper for MUMPS Library
Description: Some basic features of 'MUMPS' (Multifrontal Massively Parallel sparse direct Solver) are wrapped in a class whose methods can be used for sequentially solving a sparse linear system (symmetric or not) with one or many right hand sides (dense or sparse). There is a possibility to do separately symbolic analysis, LU (or LDL^t) factorization and system solving. Third part ordering libraries are included and can be used: 'PORD', 'METIS', 'SCOTCH'. 'MUMPS' method was first described in Amestoy et al. (2001) <doi:10.1137/S0895479899358194> and Amestoy et al. (2006) <doi:10.1016/j.parco.2005.07.004>.
Author: Serguei Sokol [aut, cre], Emmanuel Agullo [ctb], Patrick Amestoy [ctb, cph], Maurice Bremond [ctb], Alfredo Buttari [ctb], Philippe Combes [ctb], Marie Durand [ctb], Aurelia Fevre [ctb], Abdou Guermouche [ctb], Guillaume Joslin [ctb], Jacko Koster [ctb], Jean-Yves L'Excellent [ctb], Stephane Pralet [ctb], Chiara Puglisi [ctb], Francois-Henry Rouet [ctb], Wissam Sid-Lakhdar [ctb], Tzvetomila Slavova [ctb], Bora Ucar [ctb], Clement Weisbecker [ctb], Juergen Schulze [ctb], George Karypis [ctb], Douglas C. Schmidt [ctb], Isamu Hasegawa [ctb], Alexander Chemeris [ctb], Makoto Matsumoto [ctb], Takuji Nishimura [ctb], Francois Pellegrini [ctb], David Goudin [ctb], Pascal Henon [ctb], Pierre Ramet [ctb], Sebastien Fourestier [ctb], Jun-Ho Her [ctb], Cedric Chevalier [ctb], Timothy A. Davis [ctb, cph], Iain S. Duff [ctb, cph], John K. Reid [ctb, cph], Richard Stallman [ctb], Samuel Thibault [ctb, cph], CERFACS [cph], CNRS [cph], ENS Lyon [cph], INP Toulouse [cph], INRIA [cph], University of Bordeaux [cph], Regents of the University of Minnesota [cph], Free Software Foundation, Inc [cph], Alexander Chemeris [cph], Makoto Matsumoto [cph], Takuji Nishimura [cph], Universite de Bordeaux [cph], CNRS [cph], INRAE [cph]
Maintainer: Serguei Sokol <sokol@insa-toulouse.fr>

Diff between rmumps versions 5.2.1-7 dated 2019-12-06 and 5.2.1-10 dated 2020-01-28

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New package QRM with initial version 0.4-20
Package: QRM
Version: 0.4-20
Date: 2020-01-27
Title: Provides R-Language Code to Examine Quantitative Risk Management Concepts
Authors@R: c(person("Bernhard", "Pfaff", email = "bernhard@pfaffikus.de", role = c("aut", "cre")), person("Marius", "Hofert", email = "marius.hofert@math.ethz.ch", role = "ctb"), person("Alexander", "McNeil", email = "mcneil@math.ethz.ch", role = "aut", comment = "S-Plus original (QRMlib)"), person("Scott", "Ulmann", role = "trl", comment = "First R port as package QRMlib"))
Author: Bernhard Pfaff [aut, cre], Marius Hofert [ctb], Alexander McNeil [aut] (S-Plus original (QRMlib)), Scott Ulmann [trl] (First R port as package QRMlib)
Maintainer: Bernhard Pfaff <bernhard@pfaffikus.de>
Description: Provides functions/methods to accompany the book Quantitative Risk Management: Concepts, Techniques and Tools by Alexander J. McNeil, Rudiger Frey, and Paul Embrechts.
Depends: R (>= 2.10.0), gsl, Matrix, mvtnorm, numDeriv, timeSeries
Imports: Rcpp (>= 0.11.1), mgcv, methods, timeDate
LinkingTo: Rcpp
LazyData: Yes
License: GPL (>= 2)
Encoding: UTF-8
NeedsCompilation: yes
Packaged: 2020-01-27 21:39:02 UTC; bp
Repository: CRAN
Date/Publication: 2020-01-28 09:20:03 UTC

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Package lidR updated to version 2.2.2 with previous version 2.2.1 dated 2020-01-21

Title: Airborne LiDAR Data Manipulation and Visualization for Forestry Applications
Description: Airborne LiDAR (Light Detection and Ranging) interface for data manipulation and visualization. Read/write 'las' and 'laz' files, computation of metrics in area based approach, point filtering, artificial point reduction, classification from geographic data, normalization, individual tree segmentation and other manipulations.
Author: Jean-Romain Roussel [aut, cre, cph], David Auty [aut, ctb] (Reviews the documentation), Florian De Boissieu [ctb] (Fixed bugs and improved catalog features), Andrew Sánchez Meador [ctb] (Implemented wing2015 for lassnags), Bourdon Jean-François [ctb] (Implemented sensor_tracking)
Maintainer: Jean-Romain Roussel <jean-romain.roussel.1@ulaval.ca>

Diff between lidR versions 2.2.1 dated 2020-01-21 and 2.2.2 dated 2020-01-28

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Package clubSandwich updated to version 0.4.1 with previous version 0.4.0 dated 2019-12-18

Title: Cluster-Robust (Sandwich) Variance Estimators with Small-Sample Corrections
Description: Provides several cluster-robust variance estimators (i.e., sandwich estimators) for ordinary and weighted least squares linear regression models, including the bias-reduced linearization estimator introduced by Bell and McCaffrey (2002) <http://www.statcan.gc.ca/pub/12-001-x/2002002/article/9058-eng.pdf> and developed further by Pustejovsky and Tipton (2017) <DOI:10.1080/07350015.2016.1247004>. The package includes functions for estimating the variance- covariance matrix and for testing single- and multiple- contrast hypotheses based on Wald test statistics. Tests of single regression coefficients use Satterthwaite or saddle-point corrections. Tests of multiple- contrast hypotheses use an approximation to Hotelling's T-squared distribution. Methods are provided for a variety of fitted models, including lm() and mlm objects, glm(), ivreg() (from package 'AER'), plm() (from package 'plm'), gls() and lme() (from 'nlme'), lmer() (from `lme4`), robu() (from 'robumeta'), and rma.uni() and rma.mv() (from 'metafor').
Author: James Pustejovsky [aut, cre] (<https://orcid.org/0000-0003-0591-9465>)
Maintainer: James Pustejovsky <jepusto@gmail.com>

Diff between clubSandwich versions 0.4.0 dated 2019-12-18 and 0.4.1 dated 2020-01-28

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Package cartography updated to version 2.3.0 with previous version 2.2.1 dated 2019-09-27

Title: Thematic Cartography
Description: Create and integrate maps in your R workflow. This package helps to design cartographic representations such as proportional symbols, choropleth, typology, flows or discontinuities maps. It also offers several features that improve the graphic presentation of maps, for instance, map palettes, layout elements (scale, north arrow, title...), labels or legends. See Giraud and Lambert (2017) <doi:10.1007/978-3-319-57336-6_13>.
Author: Timothée Giraud [cre, aut] (<https://orcid.org/0000-0002-1932-3323>), Nicolas Lambert [aut], Ian Fellows [cph] (no overlap algorithm for labels, from wordcloud package)
Maintainer: Timothée Giraud <timothee.giraud@cnrs.fr>

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Permanent link

Package bssm updated to version 0.1.9 with previous version 0.1.8-1 dated 2020-01-07

Title: Bayesian Inference of Non-Linear and Non-Gaussian State Space Models
Description: Efficient methods for Bayesian inference of state space models via particle Markov chain Monte Carlo and parallel importance sampling type weighted Markov chain Monte Carlo (Vihola, Helske, and Franks, 2017, <arXiv:1609.02541>). Gaussian, Poisson, binomial, or negative binomial observation densities and basic stochastic volatility models with Gaussian state dynamics, as well as general non-linear Gaussian models and discretised diffusion models are supported.
Author: Jouni Helske [aut, cre] (<https://orcid.org/0000-0001-7130-793X>), Matti Vihola [aut] (<https://orcid.org/0000-0002-8041-7222>)
Maintainer: Jouni Helske <jouni.helske@iki.fi>

Diff between bssm versions 0.1.8-1 dated 2020-01-07 and 0.1.9 dated 2020-01-28

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Package beam updated to version 2.0.1 with previous version 2.0.0 dated 2020-01-26

Title: Fast Bayesian Inference in Large Gaussian Graphical Models
Description: Fast Bayesian inference of marginal and conditional independence structures from high-dimensional data.
Author: Gwenael G.R. Leday [cre, aut], Ilaria Speranza [aut], Harry Gray [ctb]
Maintainer: Gwenael G.R. Leday <gwenael.leday@mrc-bsu.cam.ac.uk>

Diff between beam versions 2.0.0 dated 2020-01-26 and 2.0.1 dated 2020-01-28

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More information about beam at CRAN
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Package mlr3misc updated to version 0.1.7 with previous version 0.1.6 dated 2019-12-12

Title: Helper Functions for 'mlr3'
Description: Frequently used helper functions and assertions used in 'mlr3' and its companion packages. Comes with helper functions for functional programming, for printing, to work with 'data.table', as well as some generally useful 'R6' classes. This package also supersedes the package 'BBmisc'.
Author: Michel Lang [cre, aut] (<https://orcid.org/0000-0001-9754-0393>), Patrick Schratz [aut] (<https://orcid.org/0000-0003-0748-6624>)
Maintainer: Michel Lang <michellang@gmail.com>

Diff between mlr3misc versions 0.1.6 dated 2019-12-12 and 0.1.7 dated 2020-01-28

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Package fingertipsR updated to version 1.0.1 with previous version 1.0.0 dated 2020-01-07

Title: Fingertips Data for Public Health
Description: Fingertips (<http://fingertips.phe.org.uk/>) contains data for many indicators of public health in England. The underlying data is now more easily accessible by making use of the API.
Author: Sebastian Fox [aut, cre], Julian Flowers [aut, ctb], Simon Thelwall [ctb] (<https://orcid.org/0000-0002-0434-2724>), Duncan Gormansway [ctb], Carl Ganz [ctb], David Whiting [ctb], Crown Copyright 2018 [cph]
Maintainer: Sebastian Fox <sebastian.fox@phe.gov.uk>

Diff between fingertipsR versions 1.0.0 dated 2020-01-07 and 1.0.1 dated 2020-01-28

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Package rredlist updated to version 0.6.0 with previous version 0.5.0 dated 2018-07-19

Title: 'IUCN' Red List Client
Description: 'IUCN' Red List (<http://apiv3.iucnredlist.org/api/v3/docs>) client. The 'IUCN' Red List is a global list of threatened and endangered species. Functions cover all of the Red List 'API' routes. An 'API' key is required.
Author: Scott Chamberlain [aut, cre], rOpenSci [fnd] (https://ropensci.org/), Maëlle Salmon [ctb]
Maintainer: Scott Chamberlain <myrmecocystus@gmail.com>

Diff between rredlist versions 0.5.0 dated 2018-07-19 and 0.6.0 dated 2020-01-28

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Package pomp updated to version 2.5 with previous version 2.4 dated 2019-10-21

Title: Statistical Inference for Partially Observed Markov Processes
Description: Tools for data analysis with partially observed Markov process (POMP) models (also known as stochastic dynamical systems, hidden Markov models, and nonlinear, non-Gaussian, state-space models). The package provides facilities for implementing POMP models, simulating them, and fitting them to time series data by a variety of frequentist and Bayesian methods. It is also a versatile platform for implementation of inference methods for general POMP models.
Author: Aaron A. King [aut, cre], Edward L. Ionides [aut], Carles Breto [aut], Stephen P. Ellner [ctb], Matthew J. Ferrari [ctb], Bruce E. Kendall [ctb], Michael Lavine [ctb], Dao Nguyen [ctb], Daniel C. Reuman [ctb], Helen Wearing [ctb], Simon N. Wood [ctb], Sebastian Funk [ctb], Steven G. Johnson [ctb], Eamon O'Dea [ctb]
Maintainer: Aaron A. King <kingaa@umich.edu>

Diff between pomp versions 2.4 dated 2019-10-21 and 2.5 dated 2020-01-28

 DESCRIPTION            |   20 +--
 MD5                    |  279 ++++++++++++++++++++++++-------------------------
 R/abc.R                |   15 --
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 R/basic_probes.R       |    9 -
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 142 files changed, 2278 insertions(+), 1297 deletions(-)

More information about pomp at CRAN
Permanent link

Package emmeans updated to version 1.4.4 with previous version 1.4.3.01 dated 2019-11-28

Title: Estimated Marginal Means, aka Least-Squares Means
Description: Obtain estimated marginal means (EMMs) for many linear, generalized linear, and mixed models. Compute contrasts or linear functions of EMMs, trends, and comparisons of slopes. Plots and other displays. Least-squares means are discussed, and the term "estimated marginal means" is suggested, in Searle, Speed, and Milliken (1980) Population marginal means in the linear model: An alternative to least squares means, The American Statistician 34(4), 216-221 <doi:10.1080/00031305.1980.10483031>.
Author: Russell Lenth [aut, cre, cph], Henrik Singmann [ctb], Jonathon Love [ctb], Paul Buerkner [ctb], Maxime Herve [ctb]
Maintainer: Russell Lenth <russell-lenth@uiowa.edu>

Diff between emmeans versions 1.4.3.01 dated 2019-11-28 and 1.4.4 dated 2020-01-28

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Package metamedian updated to version 0.1.5 with previous version 0.1.4 dated 2019-05-19

Title: Meta-Analysis of Medians
Description: Implements several methods to meta-analyze studies that report the sample median of the outcome. When the primary studies are one-group studies, the methods of McGrath et al. (2019) <doi:10.1002/sim.8013> can be applied to estimate the pooled median. In the two-group context, the methods of McGrath et al. (2020) <doi:10.1002/bimj.201900036> can be applied to estimate the pooled raw difference of medians across groups.
Author: Sean McGrath [aut, cre] (<https://orcid.org/0000-0002-7281-3516>), XiaoFei Zhao [aut], Russell Steele [aut], Andrea Benedetti [aut] (<https://orcid.org/0000-0002-8314-9497>)
Maintainer: Sean McGrath <sean.mcgrath@mail.mcgill.ca>

Diff between metamedian versions 0.1.4 dated 2019-05-19 and 0.1.5 dated 2020-01-28

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Package ElemStatLearn (with last version 2015.6.26.2) was removed from CRAN

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

2019-08-12 2015.6.26.2
2019-03-02 2015.6.26.1
2015-06-27 2015.6.26
2012-04-10 2012.04-0
2011-02-11 0.1-7.1
2009-10-22 0.1-7
2009-02-12 0.1-6
2007-09-30 0.1-4
2007-03-08 0.1-3

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Package PTXQC (with last version 1.0.0) was removed from CRAN

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

2020-01-14 1.0.0
2019-04-16 0.92.6
2019-03-15 0.92.5
2019-02-08 0.92.4
2018-02-07 0.92.3
2017-10-13 0.92.0
2017-10-06 0.91.0
2017-08-04 0.90.0
2017-06-09 0.82.6
2017-05-04 0.82.5
2017-04-03 0.82.3
2017-02-17 0.82.2
2016-10-13 0.80.14
2016-10-11 0.80.13

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