Tue, 28 Apr 2020

Package webutils updated to version 1.1 with previous version 1.0 dated 2019-08-21

Title: Utility Functions for Developing Web Applications
Description: Parses http request data in application/json, multipart/form-data, or application/x-www-form-urlencoded format. Includes example of hosting and parsing html form data in R using either 'httpuv' or 'Rhttpd'.
Author: Jeroen Ooms
Maintainer: Jeroen Ooms <jeroen@berkeley.edu>

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More information about webutils at CRAN
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Package VGAMextra updated to version 0.0-2 with previous version 0.0-1 dated 2018-06-27

Title: Additions and Extensions of the 'VGAM' Package
Description: Extending the functionalities of the 'VGAM' package with additional functions and datasets. At present, 'VGAMextra' comprises new family functions (ffs) to estimate several time series models by maximum likelihood using Fisher scoring, unlike popular packages in CRAN relying on optim(), including ARMA-GARCH-like models, the Order-(p, d, q) ARIMAX model (non- seasonal), the Order-(p) VAR model, error correction models for cointegrated time series, and ARMA-structures with Student-t errors. For independent data, new ffs to estimate the inverse- Weibull, the inverse-gamma, the generalized beta of the second kind and the general multivariate normal distributions are available. In addition, 'VGAMextra' incorporates new VGLM-links for the mean-function, and the quantile-function (as an alternative to ordinary quantile modelling) of several 1-parameter distributions, that are compatible with the class of VGLM/VGAM family functions. Currently, only fixed-effects models are implemented. All functions are subject to change; see the NEWS for further details on the latest changes.
Author: Victor Miranda [aut, cre, cph], Thomas Yee [ctb, ths, cph]
Maintainer: Victor Miranda <v.miranda@auckland.ac.nz>

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Package sensemakr updated to version 0.1.3 with previous version 0.1.2 dated 2019-08-05

Title: Sensitivity Analysis Tools for Regression Models
Description: Implements a suite of sensitivity analysis tools that extends the traditional omitted variable bias framework and makes it easier to understand the impact of omitted variables in regression models, as discussed in Cinelli, C. and Hazlett, C. (2020), "Making Sense of Sensitivity: Extending Omitted Variable Bias." Journal of the Royal Statistical Society, Series B (Statistical Methodology) <doi:10.1111/rssb.12348>.
Author: Carlos Cinelli [aut, cre], Jeremy Ferwerda [aut], Chad Hazlett [aut], Aaron Rudkin [ctb]
Maintainer: Carlos Cinelli <carloscinelli@hotmail.com>

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Package photobiologyWavebands updated to version 0.4.4 with previous version 0.4.3 dated 2019-03-28

Title: Waveband Definitions for UV, VIS, and IR Radiation
Description: Constructors of waveband objects for commonly used biological spectral weighting functions (BSWFs) and for different wavebands describing named ranges of wavelengths in the ultraviolet (UV), visible (VIS) and infrared (IR) regions of the electromagnetic spectrum. Part of the 'r4photobiology' suite, Aphalo P. J. (2015) <doi:10.19232/uv4pb.2015.1.14>.
Author: Pedro J. Aphalo [aut, cre] (<https://orcid.org/0000-0003-3385-972X>), Titta K. Kotilainen [ctb] (<https://orcid.org/0000-0002-2822-9734>)
Maintainer: Pedro J. Aphalo <pedro.aphalo@helsinki.fi>

Diff between photobiologyWavebands versions 0.4.3 dated 2019-03-28 and 0.4.4 dated 2020-04-28

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Package CA3variants updated to version 2.5 with previous version 2.0 dated 2019-08-01

Title: Three-Way Correspondence Analysis Variants
Description: Provides four variants of three-way correspondence analysis (ca): three-way symmetrical ca, three-way non-symmetrical ca, three-way ordered symmetrical ca and three-way ordered non-symmetrical ca.
Author: Rosaria Lombardo, Eric J Beh and Michel van de Velden
Maintainer: Rosaria Lombardo <rosaria.lombardo@unicampania.it>

Diff between CA3variants versions 2.0 dated 2019-08-01 and 2.5 dated 2020-04-28

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Package robustloggamma (with last version 1.0-2.1) was removed from CRAN

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

2019-04-22 1.0-2.1
2016-05-16 1.0-2
2016-05-12 1.0-1
2015-02-06 0.4-31
2013-12-19 0.4-28
2013-04-30 0.4-22
2012-11-27 0.4-19

Permanent link
Package DisImpact updated to version 0.0.8 with previous version 0.0.7 dated 2020-04-03

Title: Calculates Disproportionate Impact When Binary Success Data are Disaggregated by Subgroups
Description: Implements methods for calculating disproportionate impact: the percentage point gap, proportionality index, and the 80% index. California Community Colleges Chancellor's Office (2017). Percentage Point Gap Method. <https://www.cccco.edu/-/media/CCCCO-Website/About-Us/Divisions/Digital-Innovation-and-Infrastructure/Research/Files/PercentagePointGapMethod2017.ashx>. California Community Colleges Chancellor's Office (2014). Guidelines for Measuring Disproportionate Impact in Equity Plans. <https://www.cccco.edu/-/media/CCCCO-Website/About-Us/Divisions/Digital-Innovation-and-Infrastructure/Network-Operations/Accountability/Files/GUIDELINES-FOR-MEASURING-DISPROPORTIONATE-IMPACT-IN-EQUITY-PLANS.ashx>.
Author: Vinh Nguyen [aut, cre]
Maintainer: Vinh Nguyen <nguyenvq714@gmail.com>

Diff between DisImpact versions 0.0.7 dated 2020-04-03 and 0.0.8 dated 2020-04-28

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Package stationery updated to version 0.98.30 with previous version 0.98.24 dated 2019-11-16

Title: Working Examples for Reproducible Research Documents
Description: Templates, guides, and scripts for writing documents in 'LaTeX' and 'R markdown' to produce guides, slides, and reports. Special care is taken to illustrate use of templates and customization opportunities. Challenges and opportunities of 'HTML' output from 'R markdown' receive special attention. Includes several vignettes to assist new users of literate programming.
Author: Paul Johnson [aut, cre], Brent Kaplan [ctb], Meghan Sullivan [ctb], Charles Redmon [ctb], Zack Roman [ctb], Chong Xing [ctb], Longcan 'Emma' Huang [ctb], Garrett Mills [ctb]
Maintainer: Paul Johnson <pauljohn@ku.edu>

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Package ggspectra updated to version 0.3.6 with previous version 0.3.5 dated 2020-01-16

Title: Extensions to 'ggplot2' for Radiation Spectra
Description: Additional annotations, stats, geoms and scales for plotting "light" spectra with 'ggplot2', together with specializations of ggplot() and autoplot() methods for spectral data and waveband definitions stored in objects of classes defined in package 'photobiology'. Part of the 'r4photobiology' suite, Aphalo P. J. (2015) <doi:10.19232/uv4pb.2015.1.14>.
Author: Pedro J. Aphalo [aut, cre] (<https://orcid.org/0000-0003-3385-972X>), Titta K. Kotilainen [ctb] (<https://orcid.org/0000-0002-2822-9734>)
Maintainer: Pedro J. Aphalo <pedro.aphalo@helsinki.fi>

Diff between ggspectra versions 0.3.5 dated 2020-01-16 and 0.3.6 dated 2020-04-28

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More information about ggspectra at CRAN
Permanent link

Package npcp updated to version 0.2-0 with previous version 0.1-10 dated 2019-03-27

Title: Some Nonparametric CUSUM Tests for Change-Point Detection in Possibly Multivariate Observations
Description: Provides nonparametric CUSUM tests for detecting changes in possibly serially dependent univariate or multivariate observations. Offline tests sensitive to changes in the expectation, the variance, the covariance, the autocovariance, the distribution function, Spearman's rho, Kendall's tau, Gini's mean difference, and the copula are provided, as well as a test for detecting changes in the distribution of independent block maxima (with environmental studies in mind). The package also contains a test sensitive to changes in the autocopula and a combined test of stationarity sensitive to changes in the distribution function and the autocopula. The latest addition is a sequential test based on empirical distribution functions that can be used for monitoring changes in the contemporary distribution of possibly serially dependent univariate or multivariate observations.
Author: Ivan Kojadinovic
Maintainer: Ivan Kojadinovic <ivan.kojadinovic@univ-pau.fr>

Diff between npcp versions 0.1-10 dated 2019-03-27 and 0.2-0 dated 2020-04-28

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More information about npcp at CRAN
Permanent link

Package JWileymisc updated to version 1.1.1 with previous version 1.1.0 dated 2020-01-22

Title: Miscellaneous Utilities and Functions
Description: Miscellaneous tools and functions, including: generate descriptive statistics tables, format output, visualize relations among variables or check distributions, and generic functions for residual and model diagnostics.
Author: Joshua F. Wiley [aut, cre] (<https://orcid.org/0000-0002-0271-6702>)
Maintainer: Joshua F. Wiley <jwiley.psych@gmail.com>

Diff between JWileymisc versions 1.1.0 dated 2020-01-22 and 1.1.1 dated 2020-04-28

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Permanent link

New package tricolore with initial version 1.2.2
Package: tricolore
Type: Package
Title: A Flexible Color Scale for Ternary Compositions
Version: 1.2.2
Author: Jonas Schöley, Ilya Kashnitsky
Maintainer: Jonas Schöley <jschoeley@gmail.com>
Description: A flexible color scale for ternary compositions with options for discretization, centering and scaling.
License: GPL-3
Encoding: UTF-8
LazyData: true
Depends: R (>= 2.10)
Imports: grDevices, ggplot2 (>= 3.3.0), ggtern (>= 3.3.0), shiny, assertthat
RoxygenNote: 7.1.0
Suggests: testthat, knitr, rmarkdown, sf, leaflet, httpuv, dplyr
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2020-04-20 12:36:29 UTC; jon
Repository: CRAN
Date/Publication: 2020-04-28 13:10:02 UTC

More information about tricolore at CRAN
Permanent link

Package simplevis updated to version 1.1.1 with previous version 1.1.0 dated 2020-04-22

Title: Simple Visualisation with 'ggplot2' and 'leaflet' Wrappers
Description: Provides 'ggplot2' and 'leaflet' wrapper functions designed to simplify the creation of high quality graph and map visualisations. These functions only require inputs of data, variables and titles to provide beautiful interactive or image visualisations. However they allow for more flexibility if required. The intent is that high quality well-designed graphs and maps can be made more consistently with less effort, code and expertise than would otherwise be required.
Author: David Hodge [aut, cre] (<https://orcid.org/0000-0002-3868-7501>), Statistics New Zealand [cph]
Maintainer: David Hodge <davidhodge931@gmail.com>

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More information about simplevis at CRAN
Permanent link

Package paws updated to version 0.1.8 with previous version 0.1.7 dated 2020-03-31

Title: Amazon Web Services Software Development Kit
Description: Interface to Amazon Web Services <https://aws.amazon.com>, including storage, database, and compute services, such as 'Simple Storage Service' ('S3'), 'DynamoDB' 'NoSQL' database, and 'Lambda' functions-as-a-service.
Author: David Kretch [aut, cre], Adam Banker [aut], Amazon.com, Inc. [cph]
Maintainer: David Kretch <david.kretch@gmail.com>

Diff between paws versions 0.1.7 dated 2020-03-31 and 0.1.8 dated 2020-04-28

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More information about paws at CRAN
Permanent link

New package portalr with initial version 0.3.4
Package: portalr
Title: Create Useful Summaries of the Portal Data
Version: 0.3.4
Authors@R: c(person(given = c("Glenda", "M."), family = "Yenni", role = c("aut", "cre"), email = "glenda@weecology.org", comment = c(ORCID = "0000-0001-6969-1848")), person(given = "Hao", family = "Ye", role = "aut", comment = c(ORCID = "0000-0002-8630-1458")), person(given = c("Erica", "M."), family = "Christensen", role = "aut", comment = c(ORCID = "0000-0002-5635-2502")), person(given = c("Juniper", "L."), family = "Simonis", role = "aut", comment = c(ORCID = "0000-0001-9798-0460")), person(given = c("Ellen", "K."), family = "Bledsoe", role = "aut", comment = c(ORCID = "0000-0002-3629-7235")), person(given = c("Renata", "M."), family = "Diaz", role = "aut", comment = c(ORCID = "0000-0003-0803-4734")), person(given = c("Shawn", "D."), family = "Taylor", role = "aut", comment = c(ORCID = "0000-0002-6178-6903")), person(given = c("Ethan", "P,"), family = "White", role = "aut", comment = c(ORCID = "0000-0001-6728-7745")), person(given = c("S.K.", "Morgan"), family = "Ernest", role = "aut", comment = c(ORCID = "0000-0002-6026-8530")))
Description: Download and generate summaries for the rodent, plant, ant, and weather data from the Portal Project. Portal is a long-term (and ongoing) experimental monitoring site in the Chihuahua desert. The raw data files can be found at <https://github.com/weecology/portaldata>.
License: MIT + file LICENSE
URL: https://weecology.github.io/portalr/, https://github.com/weecology/portalr
BugReports: https://github.com/weecology/portalr/issues
Depends: R (>= 3.2.3)
Imports: clipr, clisymbols, crayon, dplyr, forecast, gh (>= 1.1.0), httr, lubridate, lunar, magrittr, rlang, tidyr, tidyselect (>= 1.0.0), zoo
Suggests: covr, cowplot, ggplot2, httptest, knitr, pkgdown, rmarkdown, testthat, usethis
VignetteBuilder: knitr
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.0
NeedsCompilation: no
Packaged: 2020-04-27 22:06:37 UTC; GlendaYenni
Author: Glenda M. Yenni [aut, cre] (<https://orcid.org/0000-0001-6969-1848>), Hao Ye [aut] (<https://orcid.org/0000-0002-8630-1458>), Erica M. Christensen [aut] (<https://orcid.org/0000-0002-5635-2502>), Juniper L. Simonis [aut] (<https://orcid.org/0000-0001-9798-0460>), Ellen K. Bledsoe [aut] (<https://orcid.org/0000-0002-3629-7235>), Renata M. Diaz [aut] (<https://orcid.org/0000-0003-0803-4734>), Shawn D. Taylor [aut] (<https://orcid.org/0000-0002-6178-6903>), Ethan P, White [aut] (<https://orcid.org/0000-0001-6728-7745>), S.K. Morgan Ernest [aut] (<https://orcid.org/0000-0002-6026-8530>)
Maintainer: Glenda M. Yenni <glenda@weecology.org>
Repository: CRAN
Date/Publication: 2020-04-28 13:20:02 UTC

More information about portalr at CRAN
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Package creditmodel updated to version 1.2 with previous version 1.1.9 dated 2020-04-20

Title: Toolkit for Credit Modeling, Analysis and Visualization
Description: Provides a highly efficient R tool suite for Credit Modeling, Analysis and Visualization. Contains infrastructure functionalities such as data exploration and preparation, missing values treatment, outliers treatment, variable derivation, variable selection, dimensionality reduction, grid search for hyper parameters, data mining and visualization, model evaluation, strategy analysis etc. This package is designed to make the development of binary classification models (machine learning based models as well as credit scorecard) simpler and faster.
Author: Dongping Fan [aut, cre]
Maintainer: Dongping Fan <fdp@pku.edu.cn>

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Permanent link

Package VGAM updated to version 1.1-3 with previous version 1.1-2 dated 2019-11-21

Title: Vector Generalized Linear and Additive Models
Description: An implementation of about 6 major classes of statistical regression models. The central algorithm is Fisher scoring and iterative reweighted least squares. At the heart of this package are the vector generalized linear and additive model (VGLM/VGAM) classes. VGLMs can be loosely thought of as multivariate GLMs. VGAMs are data-driven VGLMs that use smoothing. The book "Vector Generalized Linear and Additive Models: With an Implementation in R" (Yee, 2015) <DOI:10.1007/978-1-4939-2818-7> gives details of the statistical framework and the package. Currently only fixed-effects models are implemented. Many (150+) models and distributions are estimated by maximum likelihood estimation (MLE) or penalized MLE. The other classes are RR-VGLMs (reduced-rank VGLMs), quadratic RR-VGLMs, reduced-rank VGAMs, RCIMs (row-column interaction models)---these classes perform constrained and unconstrained quadratic ordination (CQO/UQO) models in ecology, as well as constrained additive ordination (CAO). Note that these functions are subject to change; see the NEWS and ChangeLog files for latest changes.
Author: Thomas Yee [aut, cre], Cleve Moler [ctb] (author of several LINPACK routines)
Maintainer: Thomas Yee <t.yee@auckland.ac.nz>

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New package symengine with initial version 0.1.1
Package: symengine
Title: Interface to the 'SymEngine' Library
Version: 0.1.1
Authors@R: c(person("Jialin", "Ma", email="marlin@inventati.org", role = c("cre", "aut")), person("Isuru", "Fernando", email="isuruf@gmail.com", role = c("aut")), person("Xin", "Chen", email="xinchen.tju@gmail.com", role = c("aut")))
Description: Provides an R interface to 'SymEngine' <https://github.com/symengine/>, a standalone 'C++' library for fast symbolic manipulation. The package has functionalities for symbolic computation like calculating exact mathematical expressions, solving systems of linear equations and code generation.
Depends: R (>= 3.6)
Imports: methods, Rcpp
Suggests: crayon, pracma, odeintr, testthat (>= 2.1.0), knitr, rmarkdown
LinkingTo: Rcpp
SystemRequirements: GNU make, cmake, gmp, mpfr
SystemRequirementsNote: gmp (deb package: libgmp-dev, rpm package: gmp-devel), mpfr (deb package: libmpfr-dev, rpm package: mpfr-devel)
Encoding: UTF-8
LazyData: true
URL: https://github.com/symengine/symengine.R
BugReports: https://github.com/symengine/symengine.R/issues
License: GPL (>= 2)
Copyright: The R package bundles the 'SymEngine' library source and its subcomponents under 'src/upstream' directory. See file COPYRIGHTS for retained copyright notices as a relicensing and redistribution requirement.
RoxygenNote: 7.0.2
Collate: 'RcppExports.R' 'basic-getinfo.R' 'classes.R' 'basic.R' 'codegen.R' 'double_visitor.R' 'dxdt.R' 'function_symbol.R' 'knitr.R' 'lambdify.R' 'language_conversion.R' 'matrix.R' 'misc.R' 'ops.R' 'solve.R' 'summary.R' 'symbolic_array.R' 'symengine.R' 'symengine_info.R' 'utils-subset.R' 'vector.R' 'zzz.R'
VignetteBuilder: knitr
NeedsCompilation: yes
Packaged: 2020-04-28 12:14:58 UTC; jma
Author: Jialin Ma [cre, aut], Isuru Fernando [aut], Xin Chen [aut]
Maintainer: Jialin Ma <marlin@inventati.org>
Repository: CRAN
Date/Publication: 2020-04-28 12:40:02 UTC

More information about symengine at CRAN
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Package osmose updated to version 3.3.4 with previous version 3.3.3 dated 2020-04-21

Title: Object Oriented Simulator of Marine Ecosystems
Description: The multispecies and individual-based model (IBM) 'OSMOSE' (Shin and Curry (2001) <doi:10.1016/S0990-7440(01)01106-8> and Shin and Curry (2004) <doi:10.1139/f03-154>) focuses on fish species. This model assumes opportunistic predation based on spatial co-occurrence and size adequacy between a predator and its prey (size-based opportunistic predation). It represents fish individuals grouped into schools, which are characterized by their size, weight, age, taxonomy and geographical location (2D model), and which undergo major processes of fish life cycle (growth, explicit predation, natural and starvation mortalities, reproduction and migration) and fishing exploitation. The model needs basic biological parameters that are often available for a wide range of species, and which can be found in 'FishBase' for instance (see <http://www.fishbase.org/search.php>), and fish spatial distribution data. This package provides tools to build and run simulations using the 'OSMOSE' model.
Author: Yunne-Jai Shin [aut] (<https://orcid.org/0000-0002-7259-9265>), Travers Morgane [aut] (<https://orcid.org/0000-0003-1493-662X>), Verley Philippe [aut] (<https://orcid.org/0000-0002-5686-2764>), Ricardo Oliveros-Ramos [aut] (<https://orcid.org/0000-0002-8069-2101>), Laure Velez [aut], Nicolas Barrier [cre] (<https://orcid.org/0000-0002-1693-4719>), Criscely Lujan [ctb], Michael Hurtado [ctb], Wencheng Lau-Medrano [ctb]
Maintainer: Nicolas Barrier <nicolas.barrier@ird.fr>

Diff between osmose versions 3.3.3 dated 2020-04-21 and 3.3.4 dated 2020-04-28

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Package lmSubsets updated to version 0.5 with previous version 0.4 dated 2019-03-07

Title: Exact Variable-Subset Selection in Linear Regression
Description: Exact and approximation algorithms for variable-subset selection in ordinary linear regression models. Either compute all submodels with the lowest residual sum of squares, or determine the single-best submodel according to a pre-determined statistical criterion. Hofmann et al. (2020) <10.18637/jss.v093.i03>.
Author: Marc Hofmann [aut, cre], Cristian Gatu [aut], Erricos J. Kontoghiorghes [aut], Ana Colubi [aut], Achim Zeileis [aut] (<https://orcid.org/0000-0003-0918-3766>), Martin Moene [cph] (for the GSL Lite library), Microsoft Corporation [cph] (for the GSL Lite library), Free Software Foundation, Inc. [cph] (for snippets from the GNU ISO C++ Library)
Maintainer: Marc Hofmann <marc.hofmann@gmail.com>

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Package FarmTest updated to version 2.1.0 with previous version 2.0.1 dated 2020-02-27

Title: Factor-Adjusted Robust Multiple Testing
Description: Performs robust multiple testing for means in the presence of known and unknown latent factors presented in Fan et al.(2019) "FarmTest: Factor-Adjusted Robust Multiple Testing With Approximate False Discovery Control" <doi:10.1080/01621459.2018.1527700>. Implements a series of adaptive Huber methods combined with fast data-drive tuning schemes proposed in Ke et al.(2019) "User-Friendly Covariance Estimation for Heavy-Tailed Distributions" <doi:10.1214/19-STS711> to estimate model parameters and construct test statistics that are robust against heavy-tailed and/or asymmetric error distributions. Extensions to two-sample simultaneous mean comparison problems are also included. As by-products, this package contains functions that compute adaptive Huber mean, covariance and regression estimators that are of independent interest.
Author: Xiaoou Pan [aut, cre], Yuan Ke [aut], Wen-Xin Zhou [aut]
Maintainer: Xiaoou Pan <xip024@ucsd.edu>

Diff between FarmTest versions 2.0.1 dated 2020-02-27 and 2.1.0 dated 2020-04-28

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Package DCPO updated to version 0.5.2 with previous version 0.5.1 dated 2020-04-14

Title: Dynamic Comparative Public Opinion
Description: Estimates latent variables of public opinion cross-nationally and over time from sparse and incomparable survey data. 'DCPO' uses a population-level graded response model with country-specific item bias terms. Sampling is conducted with 'Stan'. References: Solt (2020) <doi:10.31235/osf.io/d5n9p>.
Author: Frederick Solt [aut, cre], Trustees of Columbia University [cph]
Maintainer: Frederick Solt <frederick-solt@uiowa.edu>

Diff between DCPO versions 0.5.1 dated 2020-04-14 and 0.5.2 dated 2020-04-28

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Package CNVScope updated to version 3.0.8 with previous version 3.0.6 dated 2020-04-27

Title: A Versatile Toolkit for Copy Number Variation Relationship Data Analysis and Visualization
Description: Provides the ability to create interaction maps, discover CNV map domains (edges), gene annotate interactions, and create interactive visualizations of these CNV interaction maps.
Author: James Dalgeish, Yonghong Wang, Jack Zhu, Paul Meltzer
Maintainer: James Dalgleish <james.dalgleish@nih.gov>

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Package ChannelAttribution updated to version 1.18 with previous version 1.17 dated 2020-04-06

Title: Markov Model for the Online Multi-Channel Attribution Problem
Description: Advertisers use a variety of online marketing channels to reach consumers and they want to know the degree each channel contributes to their marketing success. This is called the online multi-channel attribution problem. This package contains a probabilistic algorithm for the attribution problem. The model uses a k-order Markov representation to identify structural correlations in the customer journey data. The package also contains three heuristic algorithms (first-touch, last-touch and linear-touch approach) for the same problem. The algorithms are implemented in C++.
Author: Davide Altomare, David Loris
Maintainer: Davide Altomare <davide.altomare@gmail.com>

Diff between ChannelAttribution versions 1.17 dated 2020-04-06 and 1.18 dated 2020-04-28

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Package amt updated to version 0.1.1 with previous version 0.1.0 dated 2020-04-23

Title: Animal Movement Tools
Description: Manage and analyze animal movement data. The functionality of 'amt' includes methods to calculate track statistics (e.g. step lengths, speed, or turning angles), prepare data for fitting habitat selection analyses (resource selection functions and step-selection functions <doi:10.1890/04-0953> and integrated step-selection functions <doi:10.1111/2041-210X.12528>), and simulation of space-use from fitted step-selection functions <doi:10.1002/ecs2.1771>.
Author: Johannes Signer [aut, cre], Bjoern Reineking [ctb], Brian Smith [ctb], Ulrike Schlaegel [ctb], Scott LaPoint [dtc]
Maintainer: Johannes Signer <jsigner@gwdg.de>

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New package ratPASTA with initial version 0.1.0
Package: ratPASTA
Type: Package
Title: Processing Acoustic Startle Experimental Data
Version: 0.1.0
Authors@R: c(person(given = "Ivan", family = "Kodvanj", role = c("aut", "cre"), email = "ikodvanj@gmail.com", comment = c(ORCID = "0000-0002-1359-3701")), person(given = "Davor", family = "Virag", role = c("aut"), email = "davor.virag@gmail.com", comment = c(ORCID = "0000-0003-3574-7107")), person(given = "Jan", family = "Homolak", role = c("aut"), email = "homolakjan@gmail.com", comment = c(ORCID = "0000-0003-1508-3243")))
Maintainer: Ivan Kodvanj <ikodvanj@gmail.com>
Description: Used for processing data obtained from behaviour experiments studying acoustic startle response, a reflex to a loud sound, modulated by several brain regions. The input data is generated with PASTA (Platform for Acoustic STArtle), a DIY device made from a kitchen scale that measures the twitch of an animal standing on the device and records it as time-series data. The function of this package is to import all data, process it in accordance with default or custom metadata describing the experiment protocol, calculate measurements and visualize the results. The PASTA solution and this package are described in Virag et al. (2020) <doi:10.1101/2020.04.10.035766>.
Depends: R (>= 2.10)
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.0
Imports: dplyr, ggplot2, ggpubr, ggsci, hms, lubridate, magrittr, plyr, rjson, stats, stringr, tidyr
Suggests: knitr, rmarkdown, testthat, covr
VignetteBuilder: knitr
URL: https://github.com/ikodvanj/ratPASTA
BugReports: https://github.com/ikodvanj/ratPASTA/issues
NeedsCompilation: no
Packaged: 2020-04-28 10:54:54 UTC; ivan
Author: Ivan Kodvanj [aut, cre] (<https://orcid.org/0000-0002-1359-3701>), Davor Virag [aut] (<https://orcid.org/0000-0003-3574-7107>), Jan Homolak [aut] (<https://orcid.org/0000-0003-1508-3243>)
Repository: CRAN
Date/Publication: 2020-04-28 11:40:02 UTC

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New package lazybar with initial version 0.1.0
Package: lazybar
Type: Package
Title: Progress Bar with Remaining Time Forecast Method
Version: 0.1.0
Authors@R: person("Yangzhuoran", "Yang", email = "Fin.Yang@monash.edu", role = c("aut", "cre"), comment = c(ORCID = "0000-0002-1232-8017"))
Description: A simple progress bar showing estimated remaining time. Multiple forecast methods and user defined forecast method for the remaining time are supported.
License: GPL-3
Encoding: UTF-8
LazyData: true
URL: https://pkg.yangzhuoranyang.com/lazybar/, https://github.com/FinYang/lazybar/
BugReports: https://github.com/FinYang/lazybar/issues/
Imports: R6
Suggests: forecast
RoxygenNote: 7.1.0
Language: en-AU
NeedsCompilation: no
Packaged: 2020-04-24 06:25:40 UTC; yangy
Author: Yangzhuoran Yang [aut, cre] (<https://orcid.org/0000-0002-1232-8017>)
Maintainer: Yangzhuoran Yang <Fin.Yang@monash.edu>
Repository: CRAN
Date/Publication: 2020-04-28 11:20:02 UTC

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New package eadrm with initial version 0.1.2
Package: eadrm
Title: Fitting Dose-Response Models Using an Evolutionary Algorithm
Version: 0.1.2
Authors@R: person(given = "Eric", family = "Bair", role = c("aut", "cre"), email = "eric.bair@sciome.com")
Description: Fits dose-response models using an evolutionary algorithm to estimate the model parameters. The procedure currently can fit 3-parameter, 4-parameter, and 5-parameter log-logistic models as well as exponential models. Functions are also provided to plot, make predictions, and calculate confidence intervals for the resulting models. For details see "Nonlinear Dose-response Modeling of High-Throughput Screening Data Using an Evolutionary Algorithm", Ma, J., Bair, E., Motsinger-Reif, A.; Dose-Response (In press).
Depends: R (>= 2.10.0)
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.0
NeedsCompilation: no
Packaged: 2020-04-23 15:39:15 UTC; ebair
Author: Eric Bair [aut, cre]
Maintainer: Eric Bair <eric.bair@sciome.com>
Repository: CRAN
Date/Publication: 2020-04-28 11:20:05 UTC

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New package data360r with initial version 1.0.6
Package: data360r
Type: Package
Title: Wrapper for 'TCdata360' and 'Govdata360' API
Version: 1.0.6
Authors@R: c( person("Ma. Regina Paz", "Onglao-Drilon", email = "reg@drilon.com", role = c("cre", "aut")), person("World Bank Group", email = "tcdata360@worldbank.org", role = "cph"))
Description: Makes it easy to engage with the Application Program Interface (API) of the 'TCdata360' and 'Govdata360' platforms at <https://tcdata360.worldbank.org/> and <https://govdata360.worldbank.org/>, respectively. These application program interfaces provide access to over 5000 trade, competitiveness, and governance indicator data, metadata, and related information from sources both inside and outside the World Bank Group. Package functions include easier download of data sets, metadata, and related information, as well as searching based on user-inputted query.
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
URL: https://github.com/mrpsonglao/data360r
Date: 2020-04-20
Imports: data.table, reshape2, jsonlite, utils, curl
RoxygenNote: 7.1.0
NeedsCompilation: no
Packaged: 2020-04-24 04:32:55 UTC; admin
Author: Ma. Regina Paz Onglao-Drilon [cre, aut], World Bank Group [cph]
Maintainer: Ma. Regina Paz Onglao-Drilon <reg@drilon.com>
Repository: CRAN
Date/Publication: 2020-04-28 11:20:08 UTC

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New package bcc with initial version 1.3.1
Package: bcc
Title: Beta Control Charts
Version: 1.3.1
Authors@R: c(person("Ângelo", "Santanna", role = "aut", email = "angelo.santanna@ufba.br"), person("Daniel", "Cerqueira", role = c("aut", "cre"), email = "danielcerqueira@live.com"), person("Luca", "Scrucca", role = c("ctb"), email = "luca.scrucca@unipg.it"))
Description: Applies beta control charts to defined values, using 'qcc' package with new beta control limits. The Beta Chart presents the control limits based on the Beta probability distribution. Can be used for monitoring fraction data from Binomial distribution as replacement of the p-Charts. The Beta Chart was applied for monitoring the variables in three real studies, and it was compared to the control limits with three schemes. The comparative analysis showed that: (i) Beta approximation to the Binomial distribution was more appropriate with values confined in the [0, 1]- interval; and (ii) the charts proposed were more sensitive to the average run length (ARL), in both in-control and out-of-control processes monitoring. The Beta Charts outperform the Shewhart control charts analyzed for monitoring fraction data. Ângelo Márcio Oliveira Sant’Anna, Carla Schwengber ten Caten (2012) <doi:10.1016/j.eswa.2012.02.146>.
Depends: R (>= 2.10)
URL: https://danielucas28.github.io/
License: GPL
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
Imports: qcc, methods
Suggests: knitr, rmarkdown
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2020-04-23 23:41:25 UTC; danie
Author: Ângelo Santanna [aut], Daniel Cerqueira [aut, cre], Luca Scrucca [ctb]
Maintainer: Daniel Cerqueira <danielcerqueira@live.com>
Repository: CRAN
Date/Publication: 2020-04-28 11:20:11 UTC

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New package tsriadditive with initial version 1.0.0
Package: tsriadditive
Title: Two Stage Residual Inclusion Additive Hazards Estimator
Version: 1.0.0
Authors@R: person("Andrew", "Ying", email = "aying9339@gmail.com", role = c("aut", "cre"))
Description: Additive hazards models with two stage residual inclusion method are fitted under either survival data or competing risks data. The estimator incorporates an instrumental variable and therefore can recover causal estimand in the presence of unmeasured confounding under some assumptions. A.Ying, R. Xu and J. Murphy. (2019) <doi:10.1002/sim.8071>.
Depends: R (>= 3.5.0)
Imports: survival
License: LGPL (>= 2)
Encoding: UTF-8
URL: https://onlinelibrary.wiley.com/doi/abs/10.1002/sim.8071
LazyData: true
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2020-04-23 20:06:44 UTC; andrewying
Author: Andrew Ying [aut, cre]
Maintainer: Andrew Ying <aying9339@gmail.com>
Repository: CRAN
Date/Publication: 2020-04-28 10:50:02 UTC

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Package rstatix updated to version 0.5.0 with previous version 0.4.0 dated 2020-02-13

Title: Pipe-Friendly Framework for Basic Statistical Tests
Description: Provides a simple and intuitive pipe-friendly framework, coherent with the 'tidyverse' design philosophy, for performing basic statistical tests, including t-test, Wilcoxon test, ANOVA, Kruskal-Wallis and correlation analyses. The output of each test is automatically transformed into a tidy data frame to facilitate visualization. Additional functions are available for reshaping, reordering, manipulating and visualizing correlation matrix. Functions are also included to facilitate the analysis of factorial experiments, including purely 'within-Ss' designs (repeated measures), purely 'between-Ss' designs, and mixed 'within-and-between-Ss' designs. It's also possible to compute several effect size metrics, including "eta squared" for ANOVA, "Cohen's d" for t-test and 'Cramer V' for the association between categorical variables. The package contains helper functions for identifying univariate and multivariate outliers, assessing normality and homogeneity of variances.
Author: Alboukadel Kassambara [aut, cre]
Maintainer: Alboukadel Kassambara <alboukadel.kassambara@gmail.com>

Diff between rstatix versions 0.4.0 dated 2020-02-13 and 0.5.0 dated 2020-04-28

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New package GNRS with initial version 0.1.0
Package: GNRS
Title: Access the 'Geographic Name Resolution Service'
Version: 0.1.0
Authors@R: c( person("Brad", "Boyle", email = "bboyle@email.arizona.edu", role = c("aut")), person("Brian", "Maitner", email = "bmaitner@gmail.com", role = c("aut","cre")) )
Description: Provides tools for interacting with the 'geographic name resolution service' ('GNRS') API <https://github.com/ojalaquellueva/gnrs> and associated functionality. The 'GNRS' is a batch application for resolving & standardizing political division names against standard name in the geonames database <http://www.geonames.org/>. The 'GNRS' resolves political division names at three levels: country, state/province and county/parish. Resolution is performed in a series of steps, beginning with direct matching to standard names, followed by direct matching to alternate names in different languages, followed by direct matching to standard codes (such as ISO and FIPS codes). If direct matching fails, the 'GNRS' attempts to match to standard and then alternate names using fuzzy matching, but does not perform fuzzing matching of political division codes. The 'GNRS' works down the political division hierarchy, stopping at the current level if all matches fail. In other words, if a country cannot be matched, the 'GNRS' does not attempt to match state or county.
Depends: R (>= 3.4.0)
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
Imports: rjson, RCurl, jsonlite
Suggests: knitr, rmarkdown, testthat, devtools, BIEN
VignetteBuilder: knitr
RoxygenNote: 7.1.0
NeedsCompilation: no
Packaged: 2020-04-23 18:45:47 UTC; Brian
Author: Brad Boyle [aut], Brian Maitner [aut, cre]
Maintainer: Brian Maitner <bmaitner@gmail.com>
Repository: CRAN
Date/Publication: 2020-04-28 10:40:11 UTC

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New package diseq with initial version 0.0.11
Package: diseq
Title: Estimation Methods for Markets in Disequilibrium
Version: 0.0.11
Date: 2020-04-23
Authors@R: person( "Pantelis", "Karapanagiotis", email = "pikappa.devel@gmail.com", role = c("aut", "cre"), comment = c(ORCID = "0000-0001-9871-1908"))
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.
Language: en-US
URL: https://github.com/pi-kappa-devel/diseq/
BugReports: https://github.com/pi-kappa-devel/diseq/issues
Depends: R (>= 3.5.0)
Imports: bbmle (>= 1.0.20), dplyr (>= 0.7.6), magrittr (>= 1.5), MASS (>= 7.3-50), methods, rlang (>= 0.2.1), systemfit (>= 1.1), tibble (>= 1.4.2), tidyr (>= 1.0.2)
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.0
Suggests: ggplot2 (>= 3.0.0), knitr (>= 1.20), numDeriv (>= 2016.8.1.1), rmarkdown (>= 1.10), testthat (>= 2.0.0)
VignetteBuilder: knitr
Collate: 'equation_base.R' 'system_base.R' 'equation_basic.R' 'system_basic.R' 'derivatives_basic.R' 'equation_deterministic_adjustment.R' 'system_deterministic_adjustment.R' 'derivatives_deterministic_adjustment.R' 'equation_directional.R' 'system_directional.R' 'derivatives_directional.R' 'system_fiml.R' 'derivatives_fiml.R' 'equation_stochastic_adjustment.R' 'system_stochastic_adjustment.R' 'derivatives_stochastic_adjustment.R' 'diseq.R' 'model_logger.R' 'model_base.R' 'diseq_base.R' 'diseq_basic.R' 'diseq_deterministic_adjustment.R' 'diseq_directional.R' 'diseq_stochastic_adjustment.R' 'eq_base.R' 'eq_2sls.R' 'eq_fiml.R' 'model_simulation.R'
NeedsCompilation: no
Packaged: 2020-04-23 18:27:02 UTC; ntelispak
Author: Pantelis Karapanagiotis [aut, cre] (<https://orcid.org/0000-0001-9871-1908>)
Maintainer: Pantelis Karapanagiotis <pikappa.devel@gmail.com>
Repository: CRAN
Date/Publication: 2020-04-28 10:30:02 UTC

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New package catsim with initial version 0.2.0
Package: catsim
Type: Package
Title: Binary and Categorical Image Similarity Index
Version: 0.2.0
Authors@R: c(person(c("Geoffrey", "Thompson"),email="gzthompson@gmail.com", role = c("aut", "cre"), comment = c(ORCID = '0000-0003-2436-8822')))
Description: Computes a structural similarity metric (after the style of MS-SSIM for images) for binary and categorical 2D and 3D images. Can be based on accuracy (simple matching), Cohen's kappa, Rand index, adjusted Rand index, Jaccard index, Dice index, normalized mutual information, or adjusted mutual information. In addition, has fast computation of Cohen's kappa, the Rand indices, and the two mutual informations. Implements the methods of Thompson and Maitra (2020) <arXiv:2004.09073>.
License: GPL-3
Encoding: UTF-8
LazyData: true
Imports: Rcpp
RoxygenNote: 7.1.0
URL: http://github.com/gzt/catsim, https://gzt.github.io/catsim
BugReports: https://github.com/gzt/catsim/issues
LinkingTo: Rcpp, testthat
Suggests: testthat, covr, knitr, rmarkdown
VignetteBuilder: knitr
Depends: R (>= 2.10)
NeedsCompilation: yes
Packaged: 2020-04-23 19:56:47 UTC; gzt
Author: Geoffrey Thompson [aut, cre] (<https://orcid.org/0000-0003-2436-8822>)
Maintainer: Geoffrey Thompson <gzthompson@gmail.com>
Repository: CRAN
Date/Publication: 2020-04-28 10:40:07 UTC

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New package bcTSNE with initial version 0.10.0
Package: bcTSNE
Type: Package
Title: Projected t-SNE for Batch Correction
Version: 0.10.0
Authors@R: c(person("Dayne L", "Filer", role = c("aut", "cre"), email = "dayne.filer@gmail.com"), person("Emanuele", "Aliverti", role = c("aut"), email = "aliverti@stat.unipd.it"), person("Jeff", "Tilson", role = c("aut")), person("Kirk C", "Wilhelmsen", role = c("aut")), person("David B", "Dunson", role = c("aut")))
Maintainer: Dayne L Filer <dayne.filer@gmail.com>
Description: Implements the projected t-SNE method for batch correction of high-dimensional data. Please see Aliverti et al. (2020) <doi:10.1093/bioinformatics/btaa189> for more information.
Imports: stats, RSpectra, utils, Rtsne, graphics
Suggests: data.table, batchelor, kBET, splatter, scater, knitr, lisi, harmony, dlfUtils, xtable
VignetteBuilder: knitr
SystemRequirements: GNU make
License: GPL-3
Encoding: UTF-8
LazyData: true
URL: https://github.com/emanuelealiverti/BC_tSNE
RoxygenNote: 7.0.2
Additional_repositories: https://daynefiler.github.io/drat
NeedsCompilation: yes
Packaged: 2020-04-23 16:56:25 UTC; dayne
Author: Dayne L Filer [aut, cre], Emanuele Aliverti [aut], Jeff Tilson [aut], Kirk C Wilhelmsen [aut], David B Dunson [aut]
Repository: CRAN
Date/Publication: 2020-04-28 10:20:02 UTC

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New package anglr with initial version 0.5.0
Package: anglr
Type: Package
Title: Mesh Topology and Visualization for Spatial Data
Version: 0.5.0
Authors@R: c(person("Michael D.","Sumner", role = c("aut", "cre"), email ="mdsumner@gmail.com"), person("Miles", "McBain", role = c("ctb")))
Description: Gives direct access to generic 3D tools and provides a full suite of mesh-creation and 3D plotting functions. By extending the 'rgl' package conversion and visualization functions for the 'mesh3d' class a wide variety of complex spatial data can be brought into 3D scenes. These tools allow for spatial raster, polygons, and lines that are common in 'GIS' contexts to be converted into mesh forms with high flexibility and the ability to integrate disparate data types. Vector and raster data can be seamlessly combined as meshes, and surfaces can be set to have material properties based on data values or with image textures. Textures and other data combinations use projection transformations to map between coordinate systems, and objects can be easily visualized in an interactive scene at any stage. This package relies on the 'RTriangle' package for high-quality triangular meshing which is licensed restrictively under 'CC BY-NC-SA 4.0'.
License: CC BY-NC-SA 4.0
Depends: R (>= 3.4.0)
Imports: crsmeta (>= 0.3.0), dplyr, gridBase, magrittr, palr, png, polyclip, raster, reproj (>= 0.4.2), rgl, rlang, RTriangle, scales, silicate (>= 0.4.0), sp, tibble, unjoin, utils, viridis,
Suggests: covr, ggplot2, ggpolypath, graticule, knitr, purrr, rmarkdown, sfheaders, testthat (>= 2.1.0), trip
SystemRequirements: PROJ library, OpenGL and GLU Library
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.0
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2020-04-23 20:20:31 UTC; mdsumner
Author: Michael D. Sumner [aut, cre], Miles McBain [ctb]
Maintainer: Michael D. Sumner <mdsumner@gmail.com>
Repository: CRAN
Date/Publication: 2020-04-28 10:50:05 UTC

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New package textplot with initial version 0.1.0
Package: textplot
Type: Package
Title: Text Plots
Version: 0.1.0
Maintainer: Jan Wijffels <jwijffels@bnosac.be>
Authors@R: c( person('Jan', 'Wijffels', role = c('aut', 'cre', 'cph'), email = 'jwijffels@bnosac.be'), person('BNOSAC', role = 'cph'), person("Sacha Epskamp", role = c("ctb", "cph"), comment = "code in R/matrix_reduction.R adapted from the qgraph package version 1.4.0 which is GPL-2 licensed"), person("Ingo Feinerer and Kurt Hornik", role = c("ctb", "cph"), comment = "partial code in R/textplot_corlines.R adapted from the tm package version 0.4 which is GPL-2 licensed"))
Description: Visualise complex relations in texts. This is done by providing functionalities for displaying text co-occurrence networks, text correlation networks, dependency relationships as well as text clustering. Feel free to join the effort of providing interesting text visualisations.
License: GPL-2
URL: https://github.com/bnosac/textplot
LazyData: true
Imports: utils, methods, lattice, stats, Matrix, igraph, graphics, data.table (>= 1.9.6)
Suggests: udpipe, BTM, graph, Rgraphviz, qgraph, glasso, ggplot2, ggraph, ggforce, concaveman
RoxygenNote: 7.1.0
NeedsCompilation: no
Packaged: 2020-04-22 21:13:30 UTC; Jan
Author: Jan Wijffels [aut, cre, cph], BNOSAC [cph], Sacha Epskamp [ctb, cph] (code in R/matrix_reduction.R adapted from the qgraph package version 1.4.0 which is GPL-2 licensed), Ingo Feinerer and Kurt Hornik [ctb, cph] (partial code in R/textplot_corlines.R adapted from the tm package version 0.4 which is GPL-2 licensed)
Repository: CRAN
Date/Publication: 2020-04-28 09:30:02 UTC

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New package simITS with initial version 0.1.0
Type: Package
Package: simITS
Title: Analysis via Simulation of Interrupted Time Series (ITS) Data
Version: 0.1.0
Authors@R: c(person(given = "Luke", family = "Miratrix", role = c("aut", "cre"), email = "lmiratrix@g.harvard.edu"), person(given = "Brit", family = "Henderson", role = "ctb", email = "Brit.Henderson@mdrc.org"), person(given = "Chloe", family = "Anderson", role = "ctb", email = "Chloe.AAnderson@mdrc.org"), person(given = "Arnold Ventures", role="fnd"), person(given = "MDRC", role="fnd") )
Description: Uses simulation to create prediction intervals for post-policy outcomes in interrupted time series (ITS) designs, following Miratrix (2020) <arXiv:2002.05746>. This package provides methods for fitting ITS models with lagged outcomes and variables to account for temporal dependencies. It then conducts inference via simulation, simulating a set of plausible counterfactual post-policy series to compare to the observed post-policy series. This package also provides methods to visualize such data, and also to incorporate seasonality models and smoothing and aggregation/summarization. This work partially funded by Arnold Ventures in collaboration with MDRC.
License: GPL-3
Depends: dplyr, R (>= 2.10), rlang
Suggests: arm, ggplot2, knitr, plyr, purrr, rmarkdown, stats, testthat (>= 2.1.0), tidyr
VignetteBuilder: knitr
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.0
NeedsCompilation: no
Packaged: 2020-04-22 22:10:22 UTC; lmiratrix
Author: Luke Miratrix [aut, cre], Brit Henderson [ctb], Chloe Anderson [ctb], Arnold Ventures [fnd], MDRC [fnd]
Maintainer: Luke Miratrix <lmiratrix@g.harvard.edu>
Repository: CRAN
Date/Publication: 2020-04-28 09:40:02 UTC

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New package saeeb with initial version 0.1.0
Package: saeeb
Type: Package
Title: Small Area Estimation for Count Data
Version: 0.1.0
Depends: R (>= 2.10)
Imports: COUNT (>= 1.3.4), MASS, stats
Author: Rizki Ananda Fauziah, Ika Yuni Wulansari
Maintainer: Rizki Ananda Fauziah <rizkiananda133@gmail.com>
Description: Provides small area estimation for count data type and gives option whether to use covariates in the estimation or not. By implementing Empirical Bayes (EB) Poisson-Gamma model, each function returns EB estimators and mean squared error (MSE) estimators for each area. The EB estimators without covariates are obtained using the model proposed by Clayton & Kaldor (1987) <doi:10.2307/2532003>, the EB estimators with covariates are obtained using the model proposed by Wakefield (2006) <doi:10.1093/biostatistics/kxl008> and the MSE estimators are obtained using Jackknife method by Jiang et. al. (2002) <doi:10.1214/aos/1043351257>.
License: GPL-2
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.0
NeedsCompilation: no
Packaged: 2020-04-22 20:22:06 UTC; iki
Repository: CRAN
Date/Publication: 2020-04-28 09:50:03 UTC

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New package regmed with initial version 1.0.5
Package: regmed
Type: Package
Title: Regularized Mediation Analysis
Version: 1.0.5
Date: 2020-04-22
Authors@R: c( person("Jason", "Sinnwell", email = "sinnwell.jason@mayo.edu", comment=c(ORCID="0000-0003-1964-5522"), role = c("aut","cre"),), person("Daniel", "Schaid", email = "schaid.daniel@mayo.edu", comment=c(ORCID="0000-0003-1457-6433"), role = c("aut"),), person("Gregory", "Jenkins", email="jenkins.gregory@mayo.edu", comment=c(ORCID="0000-0001-6408-6227"), role=c("ctb"),))
Description: Mediation analysis for multiple mediators by penalized structural equation models using sparse group lasso. The penalty considers the natural groupings of parameters that determine mediation, as well as encourages sparseness of the model parameters.
License: GPL (>= 2)
Depends: R (>= 3.6.0), methods, graphics, glasso
Imports: knitr, Rcpp, RcppArmadillo
Suggests: lavaan
LinkingTo: Rcpp, RcppArmadillo
NeedsCompilation: yes
VignetteBuilder: knitr
URL: https://cran.r-project.org/package=regmed
Packaged: 2020-04-22 14:34:13 UTC; sinnwell
Author: Jason Sinnwell [aut, cre] (<https://orcid.org/0000-0003-1964-5522>), Daniel Schaid [aut] (<https://orcid.org/0000-0003-1457-6433>), Gregory Jenkins [ctb] (<https://orcid.org/0000-0001-6408-6227>)
Maintainer: Jason Sinnwell <sinnwell.jason@mayo.edu>
Repository: CRAN
Date/Publication: 2020-04-28 09:20:03 UTC

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Package plotfunctions updated to version 1.4 with previous version 1.3 dated 2017-08-30

Title: Various Functions to Facilitate Visualization of Data and Analysis
Description: When analyzing data, plots are a helpful tool for visualizing data and interpreting statistical models. This package provides a set of simple tools for building plots incrementally, starting with an empty plot region, and adding bars, data points, regression lines, error bars, gradient legends, density distributions in the margins, and even pictures. The package builds further on R graphics by simply combining functions and settings in order to reduce the amount of code to produce for the user. As a result, the package does not use formula input or special syntax, but can be used in combination with default R plot functions. Note: Most of the functions were part of the package 'itsadug', which is now split in two packages: 1. the package 'itsadug', which contains the core functions for visualizing and evaluating nonlinear regression models, and 2. the package 'plotfunctions', which contains more general plot functions.
Author: Jacolien van Rij [aut, cre]
Maintainer: Jacolien van Rij <vanrij.jacolien@gmail.com>

Diff between plotfunctions versions 1.3 dated 2017-08-30 and 1.4 dated 2020-04-28

 DESCRIPTION                 |   13 
 MD5                         |  105 -
 NAMESPACE                   |    1 
 R/plot.R                    | 3052 +++++++++++++++++++++++---------------------
 R/plotfunctions.R           |    4 
 R/util.R                    |  943 +++++++------
 build/vignette.rds          |binary
 inst/NEWS                   |   17 
 inst/doc/plotfunctions.R    |   58 
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 man/getDec.Rd               |   25 
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 man/get_palette.Rd          |only
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 man/group_sort.Rd           |   27 
 man/img.Rd                  |    6 
 man/inch2coords.Rd          |   25 
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 man/marginDensityPlot.Rd    |   73 -
 man/move_n_point.Rd         |   25 
 man/orderBoxplot.Rd         |   25 
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 man/plot_signifArea.Rd      |   19 
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 man/se.Rd                   |   31 
 man/sortBoxplot.Rd          |   47 
 man/sortGroups.Rd           |   25 
 vignettes/plotfunctions.Rmd |   30 
 54 files changed, 4097 insertions(+), 2958 deletions(-)

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New package mvnormalTest with initial version 1.0.0
Package: mvnormalTest
Type: Package
Title: Powerful Tests for Multivariate Normality
Version: 1.0.0
Authors@R: c( person("Yian", "Zhang", email = "yz2777@nyu.edu", role = c("aut","cre")), person("Ming", "Zhou", email = "zhouming1027@gmail.com", role = "aut"), person("Yongzhao", "Shao", email = "yongzhao.shao@nyulangone.org", role = "aut"))
Author: Yian Zhang [aut, cre], Ming Zhou [aut], Yongzhao Shao [aut]
Maintainer: Yian Zhang <yz2777@nyu.edu>
Description: A simple informative powerful test (mvnTest()) for multivariate normality proposed by Zhou and Shao (2014) <doi:10.1080/02664763.2013.839637>, which combines kurtosis with Shapiro-Wilk test that is easy for biomedical researchers to understand and easy to implement in all dimensions. This package also contains some other multivariate normality tests including Fattorini's FA test (faTest()), Mardia's skewness and kurtosis test (mardia()), Henze-Zirkler's test (mhz()), Bowman and Shenton's test (msk()), Royston’s H test (msw()), and Villasenor-Alva and Gonzalez-Estrada's test (msw()). Empirical power calculation functions for these tests are also provided. In addition, this package includes some functions to generate several types of multivariate distributions mentioned in Zhou and Shao (2014).
License: GPL (>= 2)
Encoding: UTF-8
Imports: stats, nortest, moments, copula
Suggests: knitr
Depends: R (>= 3.5.0)
Language: en-US
RoxygenNote: 7.1.0
NeedsCompilation: no
Packaged: 2020-04-22 17:15:40 UTC; leons
Repository: CRAN
Date/Publication: 2020-04-28 09:10:02 UTC

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New package matman with initial version 1.0.0
Package: matman
Type: Package
Title: Material Management
Version: 1.0.0
Date: 2020-04-17
Authors@R: c( person("Leon", "Binder", email = "leon.binder@th-deg.de", role = c("cre", "aut")), person("Bernhard", "Bauer", email = "bernhard.bauer@th-deg.de", role = "aut"), person("Michael", "Scholz", email = "michael.scholz@th-deg.de", role = "aut"))
Maintainer: Leon Binder <leon.binder@th-deg.de>
Description: A set of functions, classes and methods for performing ABC and ABC/XYZ analyses, identifying overperforming, underperforming and constantly performing items, and plotting, analyzing as well as predicting the temporal development of items.
License: GPL-3
Depends: R (>= 3.5.0), graphics, stats, utils, dplyr, tidyr, forecast, ISOweek
Imports: methods, data.table, tidyverse
Suggests: plotly
Encoding: UTF-8
LazyData: true
LazyLoad: true
RoxygenNote: 7.1.0
NeedsCompilation: no
Packaged: 2020-04-20 11:26:49 UTC; Leon
Author: Leon Binder [cre, aut], Bernhard Bauer [aut], Michael Scholz [aut]
Repository: CRAN
Date/Publication: 2020-04-28 09:40:05 UTC

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New package XICOR with initial version 0.3.2
Package: XICOR
Type: Package
Title: Association Measurement Through Cross Rank Increments
Version: 0.3.2
Author: Susan Holmes [aut,cre], Sourav Chatterjee [aut]
Maintainer: Susan Holmes <sp.holmes@gmail.com>
Description: Computes robust association measures that do not presuppose linearity. The xi correlation (xicor) is based on cross correlation between ranked increments. The reference for the methods implemented here is Chatterjee, Sourav (2020) <arXiv:1909.10140> This package includes the Galton peas example.
Depends: R (>= 3.5.0)
License: GPL-3
Date: 2020-04-21
Encoding: UTF-8
LazyData: true
Imports: psychTools, stats
Suggests: testthat (>= 2.1.0), ggplot2
RoxygenNote: 7.1.0
NeedsCompilation: no
Packaged: 2020-04-22 15:34:30 UTC; Susan
Repository: CRAN
Date/Publication: 2020-04-28 09:00:02 UTC

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New package vizdraws with initial version 1.0.0
Package: vizdraws
Title: Visualize Draws from the Prior and Posterior Distributions
Version: 1.0.0
Date: 2020-04-22
Authors@R: c( person("Ignacio", "Martinez", email = "ignacio@protonmail.com", role = c("aut", "cre")), person("Linus", "Marco", email = "lmarco163@gmail.com", role = "aut"), person("Dan", "Thal", email = "DThal@mathematica-mpr.com", role = "aut"))
Description: Interactive visualization for Bayesian prior and posterior distributions. When both distributions are provided the animation shows a transition from prior to posterior. Finally, the animation splits the distribution using the provided 'breaks' into bars that show the probability for each region. If no 'breaks' are providers it will use zero by default.
License: GPL-3
Encoding: UTF-8
LazyData: true
URL: http://github.com/ignacio82/vizdraws, http://ignacio82.github.io/vizdraws
Imports: dplyr, tidyr, glue, htmlwidgets, magrittr, stats, stringr
RoxygenNote: 7.0.2
Suggests: knitr, rmarkdown
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2020-04-22 16:09:30 UTC; ignacio
Author: Ignacio Martinez [aut, cre], Linus Marco [aut], Dan Thal [aut]
Maintainer: Ignacio Martinez <ignacio@protonmail.com>
Repository: CRAN
Date/Publication: 2020-04-28 08:50:02 UTC

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Package superml updated to version 0.5.3 with previous version 0.5.2 dated 2020-02-24

Title: Build Machine Learning Models Like Using Python's Scikit-Learn Library in R
Description: The idea is to provide a standard interface to users who use both R and Python for building machine learning models. This package provides a scikit-learn's fit, predict interface to train machine learning models in R.
Author: Manish Saraswat [aut, cre]
Maintainer: Manish Saraswat <manish06saraswat@gmail.com>

Diff between superml versions 0.5.2 dated 2020-02-24 and 0.5.3 dated 2020-04-28

 DESCRIPTION                            |   10 
 MD5                                    |   34 +-
 NAMESPACE                              |    9 
 NEWS.md                                |    7 
 R/RcppExports.R                        |  143 +++++++++++
 R/bm25.R                               |   16 -
 R/super_utils.R                        |    9 
 README.md                              |    6 
 inst/doc/Guide-to-CountVectorizer.html |   26 +-
 inst/doc/Guide-to-TfidfVectorizer.html |   28 +-
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 src/utils.cpp                          |  340 +++++++++++++++++++++++++++
 22 files changed, 902 insertions(+), 305 deletions(-)

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Package diagonals updated to version 5.2.0 with previous version 1.0.1 dated 2020-01-08

Title: Block Diagonal Extraction or Replacement
Description: Several tools for handling block-matrix diagonals and similar constructs are implemented. Block-diagonal matrices can be extracted or removed using two small functions implemented here. In addition, non-square matrices are supported. Block diagonal matrices occur when two dimensions of a data set are combined along one edge of a matrix. For example, trade-flow data in the 'decompr' and 'gvc' packages have each country-industry combination occur along both edges of the matrix.
Author: Bastiaan Quast [aut, cre]
Maintainer: Bastiaan Quast <bquast@gmail.com>

Diff between diagonals versions 1.0.1 dated 2020-01-08 and 5.2.0 dated 2020-04-28

 diagonals-1.0.1/diagonals/NEWS                          |only
 diagonals-5.2.0/diagonals/DESCRIPTION                   |    8 +-
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 diagonals-5.2.0/diagonals/R/fatdiag.R                   |    4 -
 diagonals-5.2.0/diagonals/README.md                     |   18 +++--
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 diagonals-5.2.0/diagonals/man/diagonals.Rd              |    2 
 diagonals-5.2.0/diagonals/man/fatdiag.Rd                |    2 
 diagonals-5.2.0/diagonals/tests/testthat/test_fatdiag.R |    9 ++
 12 files changed, 58 insertions(+), 61 deletions(-)

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Package gridSVG updated to version 1.7-2 with previous version 1.7-1 dated 2019-03-29

Title: Export 'grid' Graphics as SVG
Description: Functions to export graphics drawn with package grid to SVG format. Additional functions provide access to SVG features that are not available in standard R graphics, such as hyperlinks, animation, filters, masks, clipping paths, and gradient and pattern fills.
Author: Paul Murrell [cre, aut], Simon Potter [aut]
Maintainer: Paul Murrell <paul@stat.auckland.ac.nz>

Diff between gridSVG versions 1.7-1 dated 2019-03-29 and 1.7-2 dated 2020-04-28

 DESCRIPTION                |    7 +++----
 MD5                        |   22 +++++++++++-----------
 R/animate.R                |   39 +++++++++++++++++++--------------------
 R/griddev.R                |    2 +-
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 R/svg.R                    |   14 +++-----------
 build/vignette.rds         |binary
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 inst/doc/extensibility.pdf |binary
 inst/doc/gridSVG.pdf       |binary
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 12 files changed, 58 insertions(+), 67 deletions(-)

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Package flora updated to version 0.3.4 with previous version 0.3.0 dated 2017-12-04

Title: Tools for Interacting with the Brazilian Flora 2020
Description: Tools to quickly compile taxonomic and distribution data from the Brazilian Flora 2020.
Author: Gustavo Carvalho
Maintainer: Gustavo Carvalho <gustavo.bio@gmail.com>

Diff between flora versions 0.3.0 dated 2017-12-04 and 0.3.4 dated 2020-04-28

 DESCRIPTION         |    8 ++++----
 MD5                 |   26 ++++++++++++++------------
 NAMESPACE           |    1 +
 NEWS                |   20 ++++++++++++++++++++
 R/get.synonyms.R    |   30 ++++++++++++++++++++++--------
 R/get.taxa.R        |   19 +++++++++++++++++--
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 15 files changed, 98 insertions(+), 46 deletions(-)

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Package eimpute updated to version 0.1.1 with previous version 0.1.0 dated 2020-03-20

Title: Efficiently Impute Large Scale Incomplete Matrix
Description: Efficiently impute large scale matrix with missing values via its unbiased low-rank matrix approximation. Our main approach is Hard-Impute algorithm proposed in <http://www.jmlr.org/papers/v11/mazumder10a.html>, which achieves highly computational advantage by truncated singular-value decomposition.
Author: Zhe Gao [aut, cre], Jin Zhu [aut], Junxian Zhu [aut], Xueqin Wang [aut], Yixuan Qiu [cph], Gael Guennebaud [cph, ctb], Jitse Niesen [cph, ctb], Ray Gardner [ctb]
Maintainer: Zhe Gao <gaozh8@mail2.sysu.edu.cn>

Diff between eimpute versions 0.1.0 dated 2020-03-20 and 0.1.1 dated 2020-04-28

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 eimpute-0.1.1/eimpute/man/biscale.control.Rd |    2 
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 eimpute-0.1.1/eimpute/src/RcppExports.cpp    |   80 +++++++++++
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 eimpute-0.1.1/eimpute/src/matrixfit.cpp      |  183 ++++++++++++++++++++++-----
 14 files changed, 333 insertions(+), 86 deletions(-)

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