Thu, 12 Sep 2019

Package usmap updated to version 0.5.0 with previous version 0.4.0 dated 2018-09-16

Title: US Maps Including Alaska and Hawaii
Description: Obtain United States map data frames of varying region types (e.g. county, state). The map data frames include Alaska and Hawaii conveniently placed to the bottom left, as they appear in most maps of the US. Convenience functions for plotting choropleths and working with FIPS codes are also provided.
Author: Paolo Di Lorenzo [aut, cre]
Maintainer: Paolo Di Lorenzo <paolo@dilorenzo.pl>

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Package Rfssa updated to version 1.0.0 with previous version 0.0.1 dated 2019-02-11

Title: Functional Singular Spectrum Analysis
Description: Methods and tools for implementing functional singular spectrum analysis for functional time series as described in Haghbin H., Najibi, S.M., Mahmoudvand R., Trinka J., Maadooliat M. (2019). Functional singular spectrum Analysis. Manuscript submitted for publication.
Author: Hossein Haghbin [aut, cre], Seyed Morteza Najibi [aut], Jordan Trinka [aut], Mehdi Maadooliat [aut]
Maintainer: Hossein Haghbin <haghbinh@gmail.com>

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Package rflexscan updated to version 0.2.0 with previous version 0.1 dated 2019-06-14

Title: The Flexible Spatial Scan Statistic
Description: Functions for the detection of spatial clusters using the flexible spatial scan statistic developed by Tango and Takahashi (2005) <doi:10.1186/1476-072X-4-11>. This package implements a wrapper for the C routine used in the FleXScan 3.1.2 <https://sites.google.com/site/flexscansoftware/home> developed by Takahashi, Yokoyama, and Tango.
Author: Takahiro Otani, Kunihiko Takahashi
Maintainer: Takahiro Otani <otani@med.nagoya-u.ac.jp>

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Package lsasim updated to version 2.0.0 with previous version 1.0.1 dated 2017-05-10

Title: Functions to Facilitate the Simulation of Large-Scale Assessment Data
Description: Provides functions to simulate data from large-scale educational assessments, including background questionnaire data and cognitive item responses that adhere to a multiple-matrix sampled design.
Author: Tyler Matta [aut], Leslie Rutkowski [aut], David Rutkowski [aut], Yuan-Ling Linda Liaw [aut], Kondwani Kajera Mughogho [ctb], Waldir Leoncio [aut, cre]
Maintainer: Waldir Leoncio <waldir.leoncio@gmail.com>

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New package dynr with initial version 0.1.14-85
Package: dynr
Date: 2019-09-12
Title: Dynamic Modeling in R
Authors@R: c(person("Lu", "Ou", role="aut", email="lzo114@psu.edu"), person(c("Michael", "D."), "Hunter", role=c("aut", "cre"), email="mhunter.ou@gmail.com"), person("Sy-Miin", "Chow", role="aut"))
Author: Lu Ou [aut], Michael D. Hunter [aut, cre], Sy-Miin Chow [aut]
Maintainer: Michael D. Hunter <mhunter.ou@gmail.com>
Depends: R (>= 3.0.0), ggplot2
Imports: MASS, Matrix, numDeriv, xtable, latex2exp, grid, reshape2, plyr, mice, magrittr, Rdpack, methods
Suggests: testthat, roxygen2 (>= 3.1), knitr, rmarkdown
VignetteBuilder: knitr
Description: Intensive longitudinal data have become increasingly prevalent in various scientific disciplines. Many such data sets are noisy, multivariate, and multi-subject in nature. The change functions may also be continuous, or continuous but interspersed with periods of discontinuities (i.e., showing regime switches). The package 'dynr' (Dynamic Modeling in R) is an R package that implements a set of computationally efficient algorithms for handling a broad class of linear and nonlinear discrete- and continuous-time models with regime-switching properties under the constraint of linear Gaussian measurement functions. The discrete-time models can generally take on the form of a state- space or difference equation model. The continuous-time models are generally expressed as a set of ordinary or stochastic differential equations. All estimation and computations are performed in C, but users are provided with the option to specify the model of interest via a set of simple and easy-to-learn model specification functions in R. Model fitting can be performed using single- subject time series data or multiple-subject longitudinal data.
SystemRequirements: GNU make
NeedsCompilation: yes
License: GPL-3
LazyLoad: yes
LazyData: yes
Collate: 'dynrData.R' 'dynrRecipe.R' 'dynrModelInternal.R' 'dynrModel.R' 'dynrCook.R' 'dynrPlot.R' 'dynrFuncAddress.R' 'dynrMi.R' 'dynrTaste.R' 'dynrVersion.R' 'dataDoc.R'
RdMacros: Rdpack
Biarch: true
Version: 0.1.14-85
RoxygenNote: 5.0.1
Packaged: 2019-09-12 16:25:47 UTC; mhunter
Repository: CRAN
Date/Publication: 2019-09-12 22:40:11 UTC

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Package ctsem updated to version 3.0.4 with previous version 3.0.3 dated 2019-09-11

Title: Continuous Time Structural Equation Modelling
Description: Hierarchical continuous time state space modelling, for linear and nonlinear systems measured by continuous variables, with limited support for binary data. The subject specific dynamic system is modelled as a stochastic differential equation (SDE), measurement models are typically multivariate normal factor models. Using the original ctsem formulation based on OpenMx, described in the JSS paper "Continuous Time Structural Equation Modeling with R Package ctsem", with updated version as CRAN vignette <https://cran.r-project.org/web/packages/ctsem/vignettes/ctsem.pdf> , linear mixed effects SDE's estimated via maximum likelihood and optimization are possible. Using the Stan based formulation, described in <https://github.com/cdriveraus/ctsem/raw/master/vignettes/hierarchicalmanual.pdf> , nonlinearity (state dependent parameters) and random effects on all parameters are possible, using either optimization (with optional importance sampling) or Stan's Hamiltonian Monte Carlo sampling. Priors may be used. For the conceptual overview of the hierarchical Bayesian linear SDE approach, see <https://www.researchgate.net/publication/324093594_Hierarchical_Bayesian_Continuous_Time_Dynamic_Modeling>. Exogenous inputs may also be included, for an overview of such possibilities see <https://www.researchgate.net/publication/328221807_Understanding_the_Time_Course_of_Interventions_with_Continuous_Time_Dynamic_Models> . Stan based functions are not available on 32 bit Windows systems at present.
Author: Charles Driver [aut, cre, cph], Manuel Voelkle [aut, cph], Han Oud [aut, cph], Trustees of Columbia University [cph]
Maintainer: Charles Driver <driver@mpib-berlin.mpg.de>

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Package SSDforR updated to version 1.5.8 with previous version 1.5.7 dated 2019-07-12

Title: Functions to Analyze Single System Data
Description: Functions to visually and statistically analyze single system data.
Author: Charles Auerbach [aut, cre], Wendy Zeitlin [aut]
Maintainer: Charles Auerbach <auerbach@yu.edu>

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Package MVar.pt updated to version 2.1.0 with previous version 2.0.9 dated 2019-08-27

Title: Analise multivariada (brazilian portuguese)
Description: Pacote para analise multivariada, tendo funcoes que executam analise de correspondencia simples (CA) e multipla (MCA), analise de componentes principais (PCA), analise de correlacao canonica (CCA), analise fatorial (FA), escalonamento multidimensional (MDS), analise discriminante linear (LDA) e quadratica (QDA), analise de cluster hierarquico e nao hierarquico, regressao linear simples e multipla, analise de multiplos fatores (MFA) para dados quantitativos, qualitativos, de frequencia (MFACT) e dados mistos, projection pursuit (PP), grant tour e outras funcoes uteis para a analise multivariada.
Author: Paulo Cesar Ossani <ossanipc@hotmail.com> Marcelo Angelo Cirillo <macufla@des.ufla.br>
Maintainer: Paulo Cesar Ossani <ossanipc@hotmail.com>

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Package MVar updated to version 2.1.0 with previous version 2.0.9 dated 2019-08-28

Title: Multivariate Analysis
Description: Package for multivariate analysis, having functions that perform simple correspondence analysis (CA) and multiple correspondence analysis (MCA), principal components analysis (PCA), canonical correlation analysis (CCA), factorial analysis (FA), multidimensional scaling (MDS), linear (LDA) and quadratic discriminant analysis (QDA), hierarchical and non-hierarchical cluster analysis, simple and multiple linear regression, multiple factor analysis (MFA) for quantitative, qualitative, frequency (MFACT) and mixed data, projection pursuit (PP), grant tour method and other useful functions for the multivariate analysis.
Author: Paulo Cesar Ossani <ossanipc@hotmail.com> Marcelo Angelo Cirillo <macufla@des.ufla.br>
Maintainer: Paulo Cesar Ossani <ossanipc@hotmail.com>

Diff between MVar versions 2.0.9 dated 2019-08-28 and 2.1.0 dated 2019-09-12

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Package ggspectra updated to version 0.3.4 with previous version 0.3.3.1 dated 2019-06-13

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>

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Package wevid updated to version 0.6.2 with previous version 0.6.1 dated 2019-05-13

Title: Quantifying Performance of a Binary Classifier Through Weight of Evidence
Description: The distributions of the weight of evidence (log Bayes factor) favouring case over noncase status in a test dataset (or test folds generated by cross-validation) can be used to quantify the performance of a diagnostic test (McKeigue (2019), <doi:10.1177/0962280218776989>). The package can be used with any test dataset on which you have observed case-control status and have computed prior and posterior probabilities of case status using a model learned on a training dataset. To quantify how the predictor will behave as a risk stratifier, the quantiles of the distributions of weight of evidence in cases and controls can be calculated and plotted.
Author: Paul McKeigue [aut] (<https://orcid.org/0000-0002-5217-1034>), Marco Colombo [ctb, cre] (<https://orcid.org/0000-0001-6672-0623>)
Maintainer: Marco Colombo <mar.colombo13@gmail.com>

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Package spnn updated to version 1.2 with previous version 1.1 dated 2018-03-20

Title: Scale Invariant Probabilistic Neural Networks
Description: Scale invariant version of the original PNN proposed by Specht (1990) <doi:10.1016/0893-6080(90)90049-q> with the added functionality of allowing for smoothing along multiple dimensions while accounting for covariances within the data set. It is written in the R statistical programming language. Given a data set with categorical variables, we use this algorithm to estimate the probabilities of a new observation vector belonging to a specific category. This type of neural network provides the benefits of fast training time relative to backpropagation and statistical generalization with only a small set of known observations.
Author: Romin Ebrahimi
Maintainer: Romin Ebrahimi <romin.ebrahimi@utexas.edu>

Diff between spnn versions 1.1 dated 2018-03-20 and 1.2 dated 2019-09-12

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Package ClimMobTools updated to version 0.2-7 with previous version 0.2-6 dated 2019-08-07

Title: Tools for Crowdsourcing Citizen Science in Agriculture
Description: Toolkit for the 'ClimMob' platform in R. 'ClimMob' is an open source software for crowdsourcing citizen science in agriculture <https://climmob.net/climmob3/>. Developed by van Etten et al. (2019) <doi:10.1017/S0014479716000739>, it turns the research paradigm on its head; instead of a few researchers designing complicated trials to compare several technologies in search of the best solutions, it enables many farmers to carry out reasonably simple experiments that taken together can offer even more information. 'ClimMobTools' enables project managers to deep explore and analyse their 'ClimMob' data in R.
Author: Kaue de Sousa [aut, cre] (<https://orcid.org/0000-0002-7571-7845>), Jacob van Etten [aut, ctb] (<https://orcid.org/0000-0001-7554-2558>), Sam Dumble [aut, ctb], Nicolas Greliche [aut, ctb], Brandon Madriz [aut, ctb], Carlos Quiros [aut, ctb]
Maintainer: Kaue de Sousa <kaue.desousa@inn.no>

Diff between ClimMobTools versions 0.2-6 dated 2019-08-07 and 0.2-7 dated 2019-09-12

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Package rsimsum updated to version 0.6.1 with previous version 0.6.0 dated 2019-07-15

Title: Analysis of Simulation Studies Including Monte Carlo Error
Description: Summarise results from simulation studies and compute Monte Carlo standard errors of commonly used summary statistics. This package is modelled on the 'simsum' user-written command in 'Stata' (White I.R., 2010 <http://www.stata-journal.com/article.html?article=st0200>), further extending it with additional functionality.
Author: Alessandro Gasparini [aut, cre] (<https://orcid.org/0000-0002-8319-7624>), Ian R. White [aut]
Maintainer: Alessandro Gasparini <ag475@leicester.ac.uk>

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Package pointblank updated to version 0.2.1 with previous version 0.2.0 dated 2018-05-02

Title: Validation of Local and Remote Data Tables
Description: Validate data in data frames, 'tibble' objects, in 'CSV' and 'TSV' files, and in database tables ('PostgreSQL' and 'MySQL'). Validation pipelines can be made using easily-readable, consecutive validation steps and such pipelines allow for switching of the data table context. Upon execution of the validation plan, several reporting options are available. User-defined thresholds for failure rates allow for the determination of appropriate reporting actions.
Author: Richard Iannone [aut, cre] (<https://orcid.org/0000-0003-3925-190X>)
Maintainer: Richard Iannone <riannone@me.com>

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Package MixAll updated to version 1.5.1 with previous version 1.4.2 dated 2018-04-08

Title: Clustering and Classification using Model-Based Mixture Models
Description: Algorithms and methods for model-based clustering and classification. It supports various types of data: continuous, categorical and counting and can handle mixed data of these types. It can fit Gaussian (with diagonal covariance structure), gamma, categorical and Poisson models. The algorithms also support missing values. This package can be used as an independent alternative to the (not free) 'mixtcomp' software available at <https://massiccc.lille.inria.fr/>.
Author: Serge Iovleff [aut, cre], Parmeet Bathia [ctb]
Maintainer: Serge Iovleff <Serge.Iovleff@stkpp.org>

Diff between MixAll versions 1.4.2 dated 2018-04-08 and 1.5.1 dated 2019-09-12

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 MixAll-1.5.1/MixAll/DESCRIPTION                                                                             |   18 
 MixAll-1.5.1/MixAll/MD5                                                                                     |  352 ++---
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 MixAll-1.5.1/MixAll/R/IClusterPredict.R                                                                     |   29 
 MixAll-1.5.1/MixAll/R/Learners.R                                                                            |    6 
 MixAll-1.5.1/MixAll/R/MixAll.R                                                                              |   42 
 MixAll-1.5.1/MixAll/R/kmmMixedData.R                                                                        |   26 
 MixAll-1.5.1/MixAll/build/vignette.rds                                                                      |binary
 MixAll-1.5.1/MixAll/data/birds.rda                                                                          |binary
 MixAll-1.5.1/MixAll/inst/NEWS.Rd                                                                            |    7 
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 MixAll-1.5.1/MixAll/inst/include/MixAll.h                                                                   |    4 
 MixAll-1.5.1/MixAll/inst/makefile                                                                           |    5 
 MixAll-1.5.1/MixAll/inst/makevars                                                                           |    1 
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 MixAll-1.5.1/MixAll/inst/projects/Clustering/src/STK_FullStrategy.cpp                                       |   32 
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 MixAll-1.5.1/MixAll/inst/projects/Clustering/src/STK_XemStrategy.cpp                                        |    2 
 MixAll-1.5.1/MixAll/inst/projects/Clustering/src/makefile                                                   |    2 
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 MixAll-1.5.1/MixAll/inst/projects/MixAll/ClusterLauncher.h                                                  |    4 
 MixAll-1.5.1/MixAll/inst/projects/MixAll/IClusterPredictor.h                                                |   11 
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 MixAll-1.5.1/MixAll/inst/projects/MixAll/LearnLauncher.h                                                    |   12 
 MixAll-1.5.1/MixAll/inst/projects/MixAll/MixAll_Util.h                                                      |    2 
 MixAll-1.5.1/MixAll/inst/projects/MixAll/RDataHandler.h                                                     |   13 
 MixAll-1.5.1/MixAll/man/ClusterModels-class.Rd                                                              |    4 
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 MixAll-1.5.1/MixAll/man/clusterMixedData.Rd                                                                 |    4 
 MixAll-1.5.1/MixAll/man/clusterPoisson.Rd                                                                   |    6 
 MixAll-1.5.1/MixAll/man/clusterPoissonNames.Rd                                                              |    2 
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 MixAll-1.5.1/MixAll/man/kmm.Rd                                                                              |    4 
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 MixAll-1.5.1/MixAll/man/kmmNames.Rd                                                                         |    4 
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 MixAll-1.5.1/MixAll/man/missingValues-methods.Rd                                                            |    1 
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 MixAll-1.5.1/MixAll/man/show-methods.Rd                                                                     |    8 
 MixAll-1.5.1/MixAll/man/summary-methods.Rd                                                                  |   12 
 MixAll-1.5.1/MixAll/src/ClusterFacade.cpp                                                                   |    8 
 MixAll-1.5.1/MixAll/src/ClusterLauncher.cpp                                                                 |   39 
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 MixAll-1.5.1/MixAll/src/LearnLauncher.cpp                                                                   |   40 
 MixAll-1.5.1/MixAll/src/Makevars                                                                            |   11 
 MixAll-1.5.1/MixAll/src/RDataHandler.cpp                                                                    |    4 
 MixAll-1.5.1/MixAll/src/clusterMixture.cpp                                                                  |   10 
 MixAll-1.5.1/MixAll/src/computeKernel.cpp                                                                   |    2 
 MixAll-1.5.1/MixAll/src/createKernel.cpp                                                                    |    2 
 MixAll-1.5.1/MixAll/src/init_MixAll.c                                                                       |   18 
 MixAll-1.5.1/MixAll/src/learnMixture.cpp                                                                    |    6 
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 MixAll-1.5.1/MixAll/vignettes/Introduction-Mixtures.Rnw                                                     |   17 
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 MixAll-1.5.1/MixAll/vignettes/MixAll.bib                                                                    |   18 
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Package AzureStor updated to version 2.1.1 with previous version 2.1.0 dated 2019-08-03

Title: Storage Management in 'Azure'
Description: Manage storage in Microsoft's 'Azure' cloud: <https://azure.microsoft.com/services/storage>. On the admin side, 'AzureStor' includes features to create, modify and delete storage accounts. On the client side, it includes an interface to blob storage, file storage, and 'Azure Data Lake Storage Gen2': upload and download files and blobs; list containers and files/blobs; create containers; and so on. Authenticated access to storage is supported, via either a shared access key or a shared access signature (SAS). Part of the 'AzureR' family of packages.
Author: Hong Ooi [aut, cre], Microsoft [cph]
Maintainer: Hong Ooi <hongooi@microsoft.com>

Diff between AzureStor versions 2.1.0 dated 2019-08-03 and 2.1.1 dated 2019-09-12

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Package ggdemetra updated to version 0.2.1 with previous version 0.2.0 dated 2019-06-19

Title: 'ggplot2' Extension for Seasonal and Trading Day Adjustment with 'RJDemetra'
Description: Provides 'ggplot2' functions to return the results of seasonal and trading day adjustment made by 'RJDemetra'. 'RJDemetra' is an 'R' interface around 'JDemetra+' (<https://github.com/jdemetra/jdemetra-app>), the seasonal adjustment software officially recommended to the members of the European Statistical System and the European System of Central Banks.
Author: Alain Quartier-la-Tente [aut, cre]
Maintainer: Alain Quartier-la-Tente <alain.quartier@yahoo.fr>

Diff between ggdemetra versions 0.2.0 dated 2019-06-19 and 0.2.1 dated 2019-09-12

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New package competitiontoolbox with initial version 0.1.2
Package: competitiontoolbox
Type: Package
Title: A Graphical User Interface for Antitrust and Trade Practitioners
Version: 0.1.2
Author: Charles Taragin and Paulette Wolak
Maintainer: Charles Taragin <ctaragin@ftc.gov>
Depends: R (>= 2.10), antitrust (>= 0.99.11), trade (>= 0.5.4), shiny, rhandsontable
Imports: ggplot2
Description: A graphical user interface for simulating the effects of mergers, tariffs, and quotas under an assortment of different economic models. The interface is powered by the 'Shiny' web application framework from 'RStudio'.
License: Unlimited
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2019-09-08 01:01:30 UTC; ctaragin
Repository: CRAN
Date/Publication: 2019-09-12 11:30:02 UTC

More information about competitiontoolbox at CRAN
Permanent link

New package ttdo with initial version 0.0.3
Package: ttdo
Title: Extend 'tinytest' with 'diffobj'
Version: 0.0.3
Date: 2019-09-08
Author: Dirk Eddelbuettel
Maintainer: Dirk Eddelbuettel <edd@debian.org>
Description: The 'tinytest' package offers a light-weight zero-dependency unit-testing framework to which this package adds support of the 'diffobj' package for 'diff'-style comparison of R objects.
License: GPL (>= 2)
NeedsCompilation: no
Encoding: UTF-8
LazyData: true
Imports: tinytest, diffobj
RoxygenNote: 6.0.1
Packaged: 2019-09-08 13:11:04.186973 UTC; edd
Repository: CRAN
Date/Publication: 2019-09-12 10:20:02 UTC

More information about ttdo at CRAN
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Package sentometrics updated to version 0.7.0 with previous version 0.5.6 dated 2018-12-18

Title: An Integrated Framework for Textual Sentiment Time Series Aggregation and Prediction
Description: Optimized prediction based on textual sentiment, accounting for the intrinsic challenge that sentiment can be computed and pooled across texts and time in various ways. See Ardia et al. (2018) <doi:10.2139/ssrn.3067734>.
Author: Samuel Borms [aut, cre], David Ardia [aut], Keven Bluteau [aut], Kris Boudt [aut], Jeroen Van Pelt [ctb], Andres Algaba [ctb]
Maintainer: Samuel Borms <samuel.borms@unine.ch>

Diff between sentometrics versions 0.5.6 dated 2018-12-18 and 0.7.0 dated 2019-09-12

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More information about sentometrics at CRAN
Permanent link

New package readxlsb with initial version 0.1.2
Package: readxlsb
Type: Package
Title: Read 'Excel' Binary (.xlsb) Workbooks
Version: 0.1.2
Date: 2019-09-07
Authors@R: person("Michael", "Allen", role = c("aut", "cre"), email = "michael@velofrog.com")
Depends: R (>= 3.3.0)
Description: Import data from 'Excel' binary (.xlsb) workbooks into R.
License: GPL-3
URL: https://github.com/velofrog/readxlsb
BugReports: https://github.com/velofrog/readxlsb/issues
Encoding: UTF-8
Imports: Rcpp, xml2, cellranger, utils
LinkingTo: Rcpp
Suggests: knitr, rmarkdown
VignetteBuilder: knitr
RoxygenNote: 6.1.1
NeedsCompilation: yes
Packaged: 2019-09-07 19:40:32 UTC; michael77allen
Author: Michael Allen [aut, cre]
Maintainer: Michael Allen <michael@velofrog.com>
Repository: CRAN
Date/Publication: 2019-09-12 09:10:03 UTC

More information about readxlsb at CRAN
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New package miraculix with initial version 0.9.4
Package: miraculix
Version: 0.9.4
Title: Algebraic and Statistical Functions for Genetics
Author: Martin Schlather [aut, cre], Malena Erbe [aut, cre], Florian Skene [aut], Alexander Freudenberg [ctr]
Description: This is a collection of fast tools for application in quantitative genetics. For instance, the SNP matrix can be stored in a minimum of memory and the calculation of the genomic relationship matrix is based on a rapid algorithm. It also contains the window scanning approach by Kabluchko and Spodarev (2009), <doi:10.1239/aap/1240319575> to detect anomalous genomic areas <doi:10.1186/s12864-018-5009-y>. Furthermore, the package is used in the Modular Breeding Program Simulator (MoBPS, <https://github.com/tpook92/MoBPS>, <http://www.mobps.de/>). The tools are based on SIMD (Single Instruction Multiple Data, <https://en.wikipedia.org/wiki/SIMD>) and OMP (Open Multi-Processing, <https://de.wikipedia.org/wiki/OpenMP>).
Maintainer: Martin Schlather <schlather@math.uni-mannheim.de>
LinkingTo: RandomFieldsUtils
Depends: R (>= 3.0), RandomFieldsUtils (>= 0.5.3)
Imports: methods, graphics
Suggests:
License: GPL (>= 3)
Biarch: true
URL: http://ms.math.uni-mannheim.de/de/publications/software/miraculix
NeedsCompilation: yes
Packaged: 2019-09-07 14:23:58 UTC; schlather
Repository: CRAN
Date/Publication: 2019-09-12 08:20:02 UTC

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Package tidystats updated to version 0.4 with previous version 0.3 dated 2019-01-02

Title: Combine Output of Statistical Tests
Description: Produce a file containing the output of statistical tests that can be shared or used to report statistics in scientific papers.
Author: Willem Sleegers
Maintainer: Willem Sleegers <w.sleegers@me.com>

Diff between tidystats versions 0.3 dated 2019-01-02 and 0.4 dated 2019-09-12

 tidystats |only
 1 file changed

More information about tidystats at CRAN
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Package tidytree updated to version 0.2.7 with previous version 0.2.6 dated 2019-08-09

Title: A Tidy Tool for Phylogenetic Tree Data Manipulation
Description: Phylogenetic tree generally contains multiple components including node, edge, branch and associated data. 'tidytree' provides an approach to convert tree object to tidy data frame as well as provides tidy interfaces to manipulate tree data.
Author: Guangchuang Yu [aut, cre, cph] (<https://orcid.org/0000-0002-6485-8781>), Bradley Jones [ctb], Zebulun Arendsee [ctb]
Maintainer: Guangchuang Yu <guangchuangyu@gmail.com>

Diff between tidytree versions 0.2.6 dated 2019-08-09 and 0.2.7 dated 2019-09-12

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 7 files changed, 27 insertions(+), 18 deletions(-)

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Package TestDesign updated to version 0.2.5 with previous version 0.2.3 dated 2019-08-28

Title: Optimal Test Design Approach to Fixed and Adaptive Test Construction
Description: Use the optimal test design approach by Birnbaum (1968, ISBN:9781593119348) and van der Linden (2018) <doi:10.1201/9781315117430> in constructing fixed and adaptive tests. Supports the following mixed-integer programming (MIP) solver packages: 'Rsymphony', 'gurobi', 'lpSolve', and 'Rglpk'. The 'gurobi' package is not available from CRAN; see <https://www.gurobi.com/downloads>. See vignette for installing 'Rsymphony' package on Mac systems.
Author: Seung W. Choi [aut, cre] (<https://orcid.org/0000-0003-4777-5420>), Sangdon Lim [aut] (<https://orcid.org/0000-0002-2988-014X>)
Maintainer: Seung W. Choi <schoi@austin.utexas.edu>

Diff between TestDesign versions 0.2.3 dated 2019-08-28 and 0.2.5 dated 2019-09-12

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More information about TestDesign at CRAN
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Package emmeans updated to version 1.4.1 with previous version 1.4 dated 2019-08-01

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 dated 2019-08-01 and 1.4.1 dated 2019-09-12

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Permanent link

New package cobalt with initial version 3.8.0
Package: cobalt
Title: Covariate Balance Tables and Plots
Version: 3.8.0
Author: Noah Greifer [aut, cre]
Maintainer: Noah Greifer <noah.greifer@gmail.com>
Description: Generate balance tables and plots for covariates of groups preprocessed through matching, weighting or subclassification, for example, using propensity scores. Includes integration with 'MatchIt', 'twang', 'Matching', 'optmatch', 'CBPS', 'ebal', 'WeightIt', and 'designmatch' for assessing balance on the output of their preprocessing functions. Users can also specify data for balance assessment not generated through the above packages. Also included are methods for assessing balance in clustered or multiply imputed data sets or data sets with longitudinal treatments.
Depends: R (>= 3.3.0)
Imports: ggplot2 (>= 3.0.0), grid (>= 3.6.1), gtable (>= 0.3.0), gridExtra (>= 2.3.0), ggstance, crayon, backports (>= 1.1.1)
Suggests: MatchIt, WeightIt (>= 0.5.0), twang, Matching, optmatch, ebal, CBPS (>= 0.17), designmatch, optweight, mice, mlogit (>= 0.3-0), knitr, rmarkdown
License: GPL (>= 2)
Encoding: UTF-8
LazyData: true
VignetteBuilder: knitr
URL: https://github.com/ngreifer/cobalt
BugReports: https://github.com/ngreifer/cobalt/issues
NeedsCompilation: no
Packaged: 2019-09-11 22:25:54 UTC; NoahGreifer
Repository: CRAN
Date/Publication: 2019-09-12 05:30:09 UTC

More information about cobalt at CRAN
Permanent link

Package WVPlots updated to version 1.1.2 with previous version 1.1.1 dated 2019-07-24

Title: Common Plots for Analysis
Description: Select data analysis plots, under a standardized calling interface implemented on top of 'ggplot2' and 'plotly'. Plots of interest include: 'ROC', gain curve, scatter plot with marginal distributions, conditioned scatter plot with marginal densities, box and stem with matching theoretical distribution, and density with matching theoretical distribution.
Author: John Mount [aut, cre], Nina Zumel [aut], Win-Vector LLC [cph]
Maintainer: John Mount <jmount@win-vector.com>

Diff between WVPlots versions 1.1.1 dated 2019-07-24 and 1.1.2 dated 2019-09-12

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More information about WVPlots at CRAN
Permanent link

Package pangaear updated to version 0.8.2 with previous version 0.8.0 dated 2019-08-19

Title: Client for the 'Pangaea' Database
Description: Tools to interact with the 'Pangaea' Database (<https://www.pangaea.de>), including functions for searching for data, fetching 'datasets' by 'dataset' 'ID', and working with the 'Pangaea' 'OAI-PMH' service.
Author: Scott Chamberlain [aut, cre], Kara Woo [aut], Andrew MacDonald [aut], Naupaka Zimmerman [aut], Gavin Simpson [aut]
Maintainer: Scott Chamberlain <myrmecocystus@gmail.com>

Diff between pangaear versions 0.8.0 dated 2019-08-19 and 0.8.2 dated 2019-09-12

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Package imgw updated to version 0.2.0 with previous version 0.1.0 dated 2019-06-21

Title: Polish Meteorological and Hydrological Data
Description: Download Polish meteorological and hydrological data from the Institute of Meteorology and Water Management - National Research Institute (<https://dane.imgw.pl/>). This package also allows for adding geographical coordinates for each observation.
Author: Bartosz Czernecki [aut, cre] (<https://orcid.org/0000-0001-6496-1386>), Arkadiusz GÅ‚ogowski [aut] (<https://orcid.org/0000-0002-7587-8892>), Jakub Nowosad [aut] (<https://orcid.org/0000-0002-1057-3721>), IMGW-PIB [ctb] (source of the data)
Maintainer: Bartosz Czernecki <nwp@amu.edu.pl>

Diff between imgw versions 0.1.0 dated 2019-06-21 and 0.2.0 dated 2019-09-12

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Package assertable updated to version 0.2.6 with previous version 0.2.5 dated 2019-05-07

Title: Verbose Assertions for Tabular Data (Data.frames and Data.tables)
Description: Simple, flexible, assertions on data.frame or data.table objects with verbose output for vetting. While other assertion packages apply towards more general use-cases, assertable is tailored towards tabular data. It includes functions to check variable names and values, whether the dataset contains all combinations of a given set of unique identifiers, and whether it is a certain length. In addition, assertable includes utility functions to check the existence of target files and to efficiently import multiple tabular data files into one data.table.
Author: Grant Nguyen [aut, cre]
Maintainer: Grant Nguyen <grant.nguyen@gmail.com>

Diff between assertable versions 0.2.5 dated 2019-05-07 and 0.2.6 dated 2019-09-12

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More information about assertable at CRAN
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