Fri, 12 Jul 2019

Package tidypredict updated to version 0.4.0 with previous version 0.3.0 dated 2019-01-10

Title: Run Predictions Inside the Database
Description: It parses a fitted 'R' model object, and returns a formula in 'Tidy Eval' code that calculates the predictions. It works with several databases back-ends because it leverages 'dplyr' and 'dbplyr' for the final 'SQL' translation of the algorithm. It currently supports lm(), glm(), randomForest(), ranger(), earth(), xgb.Booster.complete(), cubist(), and ctree() models.
Author: Edgar Ruiz [aut, cre]
Maintainer: Edgar Ruiz <edgar@rstudio.com>

Diff between tidypredict versions 0.3.0 dated 2019-01-10 and 0.4.0 dated 2019-07-12

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More information about tidypredict at CRAN
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New package sgd with initial version 1.1.1
Package: sgd
Type: Package
Title: Stochastic Gradient Descent for Scalable Estimation
Version: 1.1.1
Authors@R: c( person("Junhyung Lyle", "Kim", email = "lylejkim@gmail.com", role = c("cre", "aut")), person("Dustin", "Tran", role = "aut"), person("Panos", "Toulis", role = "aut"), person("Tian", "Lian", role = "ctb"), person("Ye", "Kuang", role = "ctb"), person("Edoardo", "Airoldi", role = "ctb") )
Maintainer: Junhyung Lyle Kim <lylejkim@gmail.com>
Description: A fast and flexible set of tools for large scale estimation. It features many stochastic gradient methods, built-in models, visualization tools, automated hyperparameter tuning, model checking, interval estimation, and convergence diagnostics.
URL: https://github.com/airoldilab/sgd
BugReports: https://github.com/airoldilab/sgd/issues
License: GPL-2
Imports: ggplot2, MASS, methods, Rcpp (>= 0.11.3), stats
Suggests: bigmemory, glmnet, gridExtra, R.rsp, testthat
LinkingTo: BH, bigmemory, Rcpp, RcppArmadillo
LazyData: yes
VignetteBuilder: R.rsp
RoxygenNote: 6.1.1
NeedsCompilation: yes
Packaged: 2019-07-12 21:17:49 UTC; lylekim
Author: Junhyung Lyle Kim [cre, aut], Dustin Tran [aut], Panos Toulis [aut], Tian Lian [ctb], Ye Kuang [ctb], Edoardo Airoldi [ctb]
Repository: CRAN
Date/Publication: 2019-07-12 22:11:28 UTC

More information about sgd at CRAN
Permanent link

Package rsample updated to version 0.0.5 with previous version 0.0.4 dated 2019-01-07

Title: General Resampling Infrastructure
Description: Classes and functions to create and summarize different types of resampling objects (e.g. bootstrap, cross-validation).
Author: Max Kuhn [aut, cre], Fanny Chow [aut], Hadley Wickham [aut], RStudio [cph]
Maintainer: Max Kuhn <max@rstudio.com>

Diff between rsample versions 0.0.4 dated 2019-01-07 and 0.0.5 dated 2019-07-12

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Package rddensity updated to version 1.0 with previous version 0.2.2 dated 2017-08-03

Title: Manipulation Testing Based on Density Discontinuity
Description: Density discontinuity test (a.k.a. manipulation test) is commonly employed in regression discontinuity designs and other program evaluation settings to detect whether there is evidence of perfect self-selection (manipulation) around a cutoff where a treatment/policy assignment changes. This package provides tools for conducting the aforementioned statistical test: rddensity() to construct local polynomial based density discontinuity test given a prespecified cutoff, rdbwdensity() to perform bandwidth selection, and rdplotdensity() to construct density plot near the cutoff.
Author: Matias D. Cattaneo, Michael Jansson, Xinwei Ma
Maintainer: Xinwei Ma <x1ma@ucsd.edu>

Diff between rddensity versions 0.2.2 dated 2017-08-03 and 1.0 dated 2019-07-12

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More information about rddensity at CRAN
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Package lpdensity updated to version 1.0 with previous version 0.2.3 dated 2019-04-15

Title: Local Polynomial Density Estimation and Inference
Description: Without imposing stringent distributional assumptions or shape restrictions, nonparametric density estimation has been popular in economics and other social sciences for counterfactual analysis, program evaluation, and policy recommendations. This package implements a novel density estimator based on local polynomial regressions, documented in Cattaneo, Jansson and Ma (2019a, b) <arXiv:1811.11512, arXiv:1906.06529>: lpdensity() to construct local polynomial based density (and derivatives) estimator; lpbwdensity() to perform data-driven bandwidth selection; and lpdensity.plot() for density plot with robust confidence interval.
Author: Matias D. Cattaneo, Michael Jansson, Xinwei Ma
Maintainer: Xinwei Ma <x1ma@ucsd.edu>

Diff between lpdensity versions 0.2.3 dated 2019-04-15 and 1.0 dated 2019-07-12

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More information about lpdensity at CRAN
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Package lidR updated to version 2.1.0 with previous version 2.0.3 dated 2019-05-09

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

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Package RATest updated to version 0.1.5 with previous version 0.1.4 dated 2018-11-30

Title: Randomization Tests
Description: A collection of randomization tests, data sets and examples. The current version focuses on three testing problems and their implementation in empirical work. First, it facilitates the empirical researcher to test for particular hypotheses, such as comparisons of means, medians, and variances from k populations using robust permutation tests, which asymptotic validity holds under very weak assumptions, while retaining the exact rejection probability in finite samples when the underlying distributions are identical. Second, the description and implementation of a permutation test for testing the continuity assumption of the baseline covariates in the sharp regression discontinuity design (RDD) as in Canay and Kamat (2017) <https://goo.gl/UZFqt7>. More specifically, it allows the user to select a set of covariates and test the aforementioned hypothesis using a permutation test based on the Cramer-von Miss test statistic. Graphical inspection of the empirical CDF and histograms for the variables of interest is also supported in the package. Third, it provides the practitioner with an effortless implementation of a permutation test based on the martingale decomposition of the empirical process for the goodness-of-fit testing problem with an estimated nuisance parameter. An application of this testing problem is the one of testing for heterogeneous treatment effects in a randomized control trial.
Author: Mauricio Olivares-Gonzalez [aut, cre], Ignacio Sarmiento-Barbieri [aut]
Maintainer: Mauricio Olivares-Gonzalez <maurice.olivares@gmail.com>

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Package phylopath updated to version 1.1.0 with previous version 1.0.2 dated 2019-01-02

Title: Perform Phylogenetic Path Analysis
Description: A comprehensive and easy to use R implementation of confirmatory phylogenetic path analysis as described by Von Hardenberg and Gonzalez-Voyer (2012) <doi:10.1111/j.1558-5646.2012.01790.x>.
Author: Wouter van der Bijl [aut, cre]
Maintainer: Wouter van der Bijl <wouter@zoology.ubc.ca>

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Package odds.n.ends updated to version 0.1.1 with previous version 0.1.0 dated 2019-01-20

Title: Odds Ratios, Contingency Table, and Model Significance from a Generalized Linear Model Object
Description: Computes odds ratios and 95% confidence intervals from a generalized linear model object. It also computes model significance with the chi-squared statistic and p-value and it computes model fit using a contingency table to determine the percent of observations for which the model correctly predicts the value of the outcome. Calculates model sensitivity and specificity.
Author: Jenine Harris [aut, cre]
Maintainer: Jenine Harris <harrisj@wustl.edu>

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Package IRkernel updated to version 1.0.2 with previous version 1.0.1 dated 2019-05-02

Title: Native R Kernel for the 'Jupyter Notebook'
Description: The R kernel for the 'Jupyter' environment executes R code which the front-end ('Jupyter Notebook' or other front-ends) submits to the kernel via the network.
Author: Thomas Kluyver [aut, cph], Philipp Angerer [aut, cph, cre] (<https://orcid.org/0000-0002-0369-2888>), Jan Schulz [aut, cph], Karthik Ram [aut, cph]
Maintainer: Philipp Angerer <phil.angerer@gmail.com>

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Package SSDforR updated to version 1.5.7 with previous version 1.5.6 dated 2019-06-24

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 corrr updated to version 0.4.0 with previous version 0.3.2 dated 2019-04-20

Title: Correlations in R
Description: A tool for exploring correlations. It makes it possible to easily perform routine tasks when exploring correlation matrices such as ignoring the diagonal, focusing on the correlations of certain variables against others, or rearranging and visualizing the matrix in terms of the strength of the correlations.
Author: Edgar Ruiz [aut, cre], Simon Jackson [aut], Jorge Cimentada [aut]
Maintainer: Edgar Ruiz <edgararuiz@gmail.com>

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Package panelr updated to version 0.7.1 with previous version 0.7.0 dated 2019-05-16

Title: Regression Models and Utilities for Repeated Measures and Panel Data
Description: Provides an object type and associated tools for storing and wrangling panel data. Implements several methods for creating regression models that take advantage of the unique aspects of panel data. Among other capabilities, automates the "within-between" (also known as "between-within" and "hybrid") panel regression specification that combines the desirable aspects of both fixed effects and random effects econometric models and fits them as multilevel models (Allison, 2009 <doi:10.4135/9781412993869.d33>; Bell & Jones, 2015 <doi:10.1017/psrm.2014.7>). These models can also be estimated via generalized estimating equations (GEE; McNeish, 2019 <doi:10.1080/00273171.2019.1602504>) and Bayesian estimation is (optionally) supported via 'Stan'. Supports estimation of asymmetric effects models via first differences (Allison, 2019 <doi:10.1177/2378023119826441>) as well as a generalized linear model extension thereof using GEE.
Author: Jacob A. Long [aut, cre] (<https://orcid.org/0000-0002-1582-6214>)
Maintainer: Jacob A. Long <long.1377@osu.edu>

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Package optmatch updated to version 0.9-11 with previous version 0.9-10 dated 2018-07-12

Title: Functions for Optimal Matching
Description: Distance based bipartite matching using the RELAX-IV minimum cost flow solver, oriented to matching of treatment and control groups in observational studies. Routines are provided to generate distances from generalised linear models (propensity score matching), formulas giving variables on which to limit matched distances, stratified or exact matching directives, or calipers, alone or in combination.
Author: Ben B. Hansen <ben.hansen@umich.edu>, Mark Fredrickson <mark.m.fredrickson@gmail.com>, Josh Buckner, Josh Errickson, Adam Rauh and Peter Solenberger, with embedded Fortran code due to Dimitri P. Bertsekas <dimitrib@mit.edu> and Paul Tseng
Maintainer: Mark M. Fredrickson <mark.m.fredrickson@gmail.com>

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New package lda.svi with initial version 0.1.0
Package: lda.svi
Title: Fit Latent Dirichlet Allocation Models using Stochastic Variational Inference
Version: 0.1.0
Authors@R: person("Nicholas", "Erskine", email = "nicholas.erskine95@gmail.com", role = c("aut", "cre"))
Description: Fits Latent Dirichlet Allocation topic models to text data using the stochastic variational inference algorithm described in Hoffman et. al. (2013) <arXiv:1206.7051v3>. This method is more efficient than the original batch variational inference algorithm for LDA, and allows users to fit LDA models with more topics and to larger text corpora than would be feasible using that older method.
Depends: R (>= 3.5.0)
License: MIT + file LICENSE
BugReports: https://github.com/nerskin/lda.svi/issues
Encoding: UTF-8
RoxygenNote: 6.1.1
LinkingTo: Rcpp, RcppArmadillo, BH
Imports: Rcpp, reshape2, tm (>= 0.6), methods, Rdpack
Suggests: topicmodels
SystemRequirements: C++11
NeedsCompilation: yes
Packaged: 2019-07-08 13:26:49 UTC; nicholas
Author: Nicholas Erskine [aut, cre]
Maintainer: Nicholas Erskine <nicholas.erskine95@gmail.com>
Repository: CRAN
Date/Publication: 2019-07-12 16:10:02 UTC

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New package hindex with initial version 0.1.0
Package: hindex
Title: Simulating the Development of h-Index Values
Version: 0.1.0
Authors@R: c( person(given = "Alexander", family = "Tekles", role = c("aut", "cre"), email = "alexander.tekles@soziologie.uni-muenchen.de"), person(given = "Lutz", family = "Bornmann", role = "ctb"), person(given = "Christian", family = "Ganser", role = "ctb"))
Description: H-index and h-alpha are a bibliometric indicators. This package provides functions to simulate how these indicators may develop over time for a given set of researchers and to visualize the simulation data. The implementation is based on the 'STATA' ado h-index and is described in more detail in Bornmann et al. (2019) <arXiv:1905.11052>.
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
Suggests: testthat
Imports: foreach, stats, ggplot2
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2019-07-02 20:54:54 UTC; alex
Author: Alexander Tekles [aut, cre], Lutz Bornmann [ctb], Christian Ganser [ctb]
Maintainer: Alexander Tekles <alexander.tekles@soziologie.uni-muenchen.de>
Repository: CRAN
Date/Publication: 2019-07-12 16:10:05 UTC

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New package GET with initial version 0.1-3
Package: GET
Version: 0.1-3
Date: 2019-06-28
Title: Global Envelopes
Encoding: UTF-8
Authors@R: c( person(given = 'Mari', family = 'Myllymäki', role = c('aut', 'cre'), email = 'mari.myllymaki@luke.fi'), person(given = 'Tomáš', family = 'Mrkvička', role = 'aut', email = 'mrkvicka.toma@gmail.com'), person(given = 'Pavel', family = 'Grabarnik', role = 'ctb', email = 'gpya@rambler.ru'), person(given = 'Ute', family = 'Hahn', role = 'ctb', email = 'ute@math.au.dk'), person(given = 'Mikko', family = 'Kuronen', role = 'ctb', email = 'mikko.kuronen@luke.fi'), person(given = 'Michael', family = 'Rost', role = 'ctb', email = 'rost@ef.jcu.cz'), person(given = 'Henri', family = 'Seijo', role = 'ctb', email = 'henri.seijo@iki.fi') )
Maintainer: Mari Myllymäki <mari.myllymaki@luke.fi>
Imports: caTools, fda.usc, ggplot2, graphics, grDevices, gridExtra, gstat, methods, parallel, plyr, sp, spatstat, stats, utils,
Suggests: testthat, mvtnorm, fda
Description: Implementation of global envelopes with intrinsic graphical interpretation which can be used for graphical Monte Carlo and permutation tests where the test statistic is a multivariate vector or function (e.g. goodness-of-fit testing for point patterns and random sets, functional analysis of variance, functional general linear model, n-sample test of correspondence of distribution functions), for central regions of functional or multivariate data (e.g. outlier detection, functional boxplot) and for global confidence and prediction bands (e.g. confidence band in polynomial regression, Bayesian posterior prediction). See Myllymäki et al. (2017) <doi: 10.1111/rssb.12172>, Mrkvička et al. (2017) <doi: 10.1007/s11222-016-9683-9>, Mrkvička et al. (2016) <doi: 10.1016/j.spasta.2016.04.005>, Mrkvička et al. (2018) <arXiv:1612.03608>, Mrkvička et al. (2019) <arXiv:1906.09004>, Mrkvička et al. (2019) <arXiv:1902.04926>.
License: GPL-3
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2019-07-08 13:55:24 UTC; L1067
Author: Mari Myllymäki [aut, cre], Tomáš Mrkvička [aut], Pavel Grabarnik [ctb], Ute Hahn [ctb], Mikko Kuronen [ctb], Michael Rost [ctb], Henri Seijo [ctb]
Repository: CRAN
Date/Publication: 2019-07-12 16:10:08 UTC

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Package embed updated to version 0.0.3 with previous version 0.0.2 dated 2018-11-19

Title: Extra Recipes for Encoding Categorical Predictors
Description: Predictors can be converted to one or more numeric representations using simple generalized linear models <arXiv:1611.09477> or nonlinear models <arXiv:1604.06737>. All encoding methods are supervised.
Author: Max Kuhn [aut, cre], RStudio [cph]
Maintainer: Max Kuhn <max@rstudio.com>

Diff between embed versions 0.0.2 dated 2018-11-19 and 0.0.3 dated 2019-07-12

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Package XGR updated to version 1.1.6 with previous version 1.1.5 dated 2019-03-29

Title: Exploring Genomic Relations for Enhanced Interpretation Through Enrichment, Similarity, Network and Annotation Analysis
Description: The central goal of XGR by Fang et al. (2016) <doi:10.1186/s13073-016-0384-y> is to provide a data interpretation system necessary to do "big data" science. It is designed to make a user-defined gene or SNP list (or genomic regions) more interpretable by comprehensively utilising ontology annotations and interaction networks to reveal relationships and enhance opportunities for biological discovery. XGR is unique in supporting a broad range of ontologies (including knowledge of biological and molecular functions, pathways, diseases and phenotypes - in both human and mouse) and different types of networks (including functional, physical and pathway interactions). There are two core functionalities of XGR. The first is to provide basic infrastructures for easy access to built-in ontologies and networks. The second is to support data interpretations via 1) enrichment analysis using either built-in or custom ontologies, 2) similarity analysis for calculating semantic similarity between genes (or SNPs) based on their ontology annotation profiles, 3) network analysis for identification of gene networks given a query list of (significant) genes, SNPs or genomic regions, and 4) annotation analysis for interpreting genomic regions using co-localised functional genomic annotations (such as open chromatin, epigenetic marks, TF binding sites and genomic segments) and using nearby gene annotations (by ontologies). Together with its web app, XGR aims to provide a user-friendly tool for exploring genomic relations at the gene, SNP and genomic region level.
Author: Hai Fang, Bogdan Knezevic, Katie L Burnham, Julian C Knight
Maintainer: Hai Fang <hfang@well.ox.ac.uk>

Diff between XGR versions 1.1.5 dated 2019-03-29 and 1.1.6 dated 2019-07-12

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New package mipred with initial version 0.0.1
Package: mipred
Type: Package
Title: Prediction using Multiple Imputation
Version: 0.0.1
Authors@R: person("Bart J. A.", "Mertens", email = "b.mertens@lumc.nl", role = c("aut", "cre"), comment = c(ORCID = "0000-0002-5019-0354"))
Maintainer: Bart J. A. Mertens <b.mertens@lumc.nl>
Description: Calibration of generalized linear models and Cox regression models for prediction using multiple imputation to account for missing values in the predictors as described in the paper by "Mertens, Banzato and de Wreede" (2018) <arXiv:1810.05099>. The methodology and calculations described in this paper are fully implemented in this package. The vignette describes all data analytic steps which allow users to replicate results using the package functions on the data analyzed in the paper or on their own data. Imputations are generated using the package 'mice' without using the outcomes of observations for which the predictions are generated. Two options are provided to generate predictions. The first is prediction-averaging of predictions calibrated from single models fitted on single imputed datasets within a set of multiple imputations. The second is application of the Rubin's rules pooled model. For both implementations, unobserved values in the predictor data of new observations for which the predictions are derived are automatically imputed. The package contains two basic functions. The first, mipred() generates predictions of outcome on new observations. The second, mipred.cv() generates cross-validated predictions with the methodology on existing data for which outcomes have already been observed. The present version is still in development and should support continuous, binary and counting outcomes, but we have only thoroughly checked performance for binary outcome logistic regression modeling. We will include the Cox regression extension later.
URL: https://github.com/BartJAMertens/mipred, https://arxiv.org/abs/1810.05099, https://www.researchgate.net/project/Prediction-calibration-using-multiple-imputations-to-account-for-missing-predictor-values
BugReports: https://github.com/BartJAMertens/mipred/issues
Depends: R (>= 3.5.0)
License: GPL-3
Imports: mice (>= 3.4.0)
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
Suggests: testthat, knitr, rmarkdown, pROC
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2019-07-05 12:37:55 UTC; bartm
Author: Bart J. A. Mertens [aut, cre] (<https://orcid.org/0000-0002-5019-0354>)
Repository: CRAN
Date/Publication: 2019-07-12 15:50:03 UTC

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New package intervcomp with initial version 0.1.2
Package: intervcomp
Type: Package
Title: Hypothesis Testing Using the Overlapping Interval Estimates
Version: 0.1.2
Authors@R: c( person("Kimihiro", "Noguchi", email = "kimihiro.noguchi@wwu.edu", role = c("aut", "cre")), person("Ryan", "Erps", email = "ryan.aloha@yahoo.com", role = "ctb"), person("Chris", "Murphy", email = "cmurphy0313@ufl.edu", role = "ctb") )
Description: Performs hypothesis testing using the interval estimates (e.g., confidence intervals). The non-overlapping interval estimates indicates the statistical significance. References to these procedures can be found at Noguchi and Marmolejo-Ramos (2016) <doi:10.1080/00031305.2016.1200487>, Bonett and Seier (2003) <doi:10.1198/0003130032323>, and Lemm (2006) <doi:10.1300/J082v51n02_05>.
Depends:
Imports: graphics, grDevices, stats
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2019-07-07 23:54:45 UTC; blueviking
Author: Kimihiro Noguchi [aut, cre], Ryan Erps [ctb], Chris Murphy [ctb]
Maintainer: Kimihiro Noguchi <kimihiro.noguchi@wwu.edu>
Repository: CRAN
Date/Publication: 2019-07-12 16:00:03 UTC

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New package imgrec with initial version 0.1.0
Package: imgrec
Type: Package
Title: Image Recognition
Version: 0.1.0
Date: 2019-07-05
Authors@R: person("Carsten", "Schwemmer", email = "c.schwem2er@gmail.com", comment = c(ORCID = "0000-0001-9084-946X"), role = c("aut", "cre"))
URL: https://github.com/cschwem2er/imgrec
BugReports: https://github.com/cschwem2er/imgrec/issues
Description: Provides an interface for image recognition using the 'Google Vision API' <https://cloud.google.com/vision/> . Converts API data for features such as object detection and optical character recognition to data frames. The package also includes functions for analyzing image annotations.
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
Imports: knitr (>= 1.2.0), base64enc (>= 0.1.0), dplyr (>= 0.7.0), httr (>= 1.4.0), jsonlite (>= 1.6.0), rlang (>= 0.4.0)
Suggests: magick (>= 2.0.0), ggplot2 (>= 3.2.0), usethis (>= 1.5.0), pillar (>= 1.4.0), rmarkdown (>= 1.1.0)
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2019-07-05 15:41:55 UTC; kasus
Author: Carsten Schwemmer [aut, cre] (<https://orcid.org/0000-0001-9084-946X>)
Maintainer: Carsten Schwemmer <c.schwem2er@gmail.com>
Repository: CRAN
Date/Publication: 2019-07-12 15:50:06 UTC

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New package RxODE with initial version 0.9.1-0
Package: RxODE
Version: 0.9.1-0
Title: Facilities for Simulating from ODE-Based Models
Authors@R: c( person("Matthew L.","Fidler", role = "aut", email = "matthew.fidler@gmail.com", comment=c(ORCID="0000-0001-8538-6691")), person("Melissa", "Hallow", role = "aut", email = "hallowkm@uga.edu"), person("Wenping", "Wang", role = c("aut", "cre"), email = "wwang8198@gmail.com"), person("Zufar", "Mulyukov", role="ctb", email="zufar.mulyukov@novartis.com"), person("Justin", "Wilkins", role = "ctb", email = "justin.wilkins@occams.com", comment=c(ORCID="0000-0002-7099-9396")), person("Simon", "Frost", role="ctb"), person("Heng", "Li", role="ctb"), person("Yu", "Feng", role="ctb"), person("Alan", "Hindmarsh",role="ctb"), person("Linda", "Petzold", role="ctb"), person("Ernst", "Hairer", role="ctb"), person("Gerhard", "Wanner", role="ctb"), person("J", "Colinge", role="ctb"), person("Hadley", "Wickham", role="ctb"), person("G", "Grothendieck", role="ctb"), person("Robert", "Gentleman",role="ctb"), person("Ross", "Ihaka",role="ctb"), person("R core team", role="cph"), person("odepack authors", role="cph") )
Maintainer: Wenping Wang <wwang8198@gmail.com>
Depends: R (>= 3.4.0)
Suggests: knitr, DT, nlme, shiny, tcltk, testthat, usethis, devtools, covr, rmarkdown, SnakeCharmR, dplyr (>= 0.8.0), tidyr, tibble, curl, gridExtra, microbenchmark, scales, stringi, htmltools, reticulate, rlang, installr
Imports: Matrix, PreciseSums (>= 0.3), Rcpp (>= 0.12.3), brew, cli, crayon, digest, dparser (>= 0.1.8), ggforce, ggplot2, inline, magrittr, memoise, methods, mvnfast, n1qn1 (>= 6.0.1-2), pillar, rex, sys, units(>= 0.6-0), utils, assertthat, lotri, remotes
Description: Facilities for running simulations from ordinary differential equation (ODE) models, such as pharmacometrics and other compartmental models. A compilation manager translates the ODE model into C, compiles it, and dynamically loads the object code into R for improved computational efficiency. An event table object facilitates the specification of complex dosing regimens (optional) and sampling schedules. NB: The use of this package requires both C and Fortran compilers, for details on their use with R please see Section 6.3, Appendix A, and Appendix D in the "R Administration and Installation" manual. Also the code is mostly released under GPL. The VODE and LSODA are in the public domain. The information is available in the inst/COPYRIGHTS.
BugReports: https://github.com/nlmixrdevelopment/RxODE/issues
NeedsCompilation: yes
VignetteBuilder: knitr
License: GPL (>= 2)
URL: https://nlmixrdevelopment.github.io/RxODE/
RoxygenNote: 6.1.1
Biarch: true
LinkingTo: dparser(>= 0.1.8), Rcpp (>= 0.12.3), RcppArmadillo(>= 0.9.300.2.0), PreciseSums (>= 0.3)
Encoding: UTF-8
LazyData: true
Packaged: 2019-07-12 12:09:16 UTC; wangwez
Author: Matthew L. Fidler [aut] (<https://orcid.org/0000-0001-8538-6691>), Melissa Hallow [aut], Wenping Wang [aut, cre], Zufar Mulyukov [ctb], Justin Wilkins [ctb] (<https://orcid.org/0000-0002-7099-9396>), Simon Frost [ctb], Heng Li [ctb], Yu Feng [ctb], Alan Hindmarsh [ctb], Linda Petzold [ctb], Ernst Hairer [ctb], Gerhard Wanner [ctb], J Colinge [ctb], Hadley Wickham [ctb], G Grothendieck [ctb], Robert Gentleman [ctb], Ross Ihaka [ctb], R core team [cph], odepack authors [cph]
Repository: CRAN
Date/Publication: 2019-07-12 14:20:07 UTC

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New package qMRI with initial version 1.0.1
Package: qMRI
Type: Package
Title: Methods for Quantitative Magnetic Resonance Imaging ('qMRI')
Version: 1.0.1
Date: 2019-07-12
Authors@R: c(person("Joerg", "Polzehl", role = c("aut"), email = "joerg.polzehl@wias-berlin.de"), person("Karsten", "Tabelow", role = c("aut", "cre"), email = "karsten.tabelow@wias-berlin.de"), person("WIAS Berlin", role = c("cph", "fnd")))
Maintainer: Karsten Tabelow <karsten.tabelow@wias-berlin.de>
Depends: R (>= 3.1), awsMethods (>= 1.0)
Imports: oro.nifti (>= 0.9), stringr, dti (>= 1.4), aws (>= 2.2), adimpro (>= 0.9)
LazyData: TRUE
Description: Implementation of methods for estimation of quantitative maps from Multi-Parameter Mapping (MPM) acquisitions (Weiskopf et al. (2013) <doi:10.3389/fnins.2013.00095>) including adaptive smoothing methods in the framework of the ESTATICS model (Estimating the apparent transverse relaxation time (R2*) from images with different contrasts, Weiskopf et al. (2014) <doi:10.3389/fnins.2014.00278>). The smoothing method is described in Mohammadi et al. (2017). <doi:10.20347/WIAS.PREPRINT.2432>.
License: GPL (>= 2)
Copyright: This package is Copyright (C) 2015-2019 Weierstrass Institute for Applied Analysis and Stochastics.
URL: http://www.wias-berlin.de/research/ats/imaging/
Suggests: covr, testthat, knitr, rmarkdown
VignetteBuilder: knitr
RoxygenNote: 6.1.1
NeedsCompilation: yes
Packaged: 2019-07-12 12:28:45 UTC; polzehl
Author: Joerg Polzehl [aut], Karsten Tabelow [aut, cre], WIAS Berlin [cph, fnd]
Repository: CRAN
Date/Publication: 2019-07-12 14:20:03 UTC

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New package paradox with initial version 0.1.0
Type: Package
Package: paradox
Title: Define and Work with Parameter Spaces for Complex Algorithms
Version: 0.1.0
Authors@R: c(person(given = "Michel", family = "Lang", role = c("cre", "aut"), email = "michellang@gmail.com", comment = c(ORCID = "0000-0001-9754-0393")), person(given = "Bernd", family = "Bischl", role = "aut", email = "bernd_bischl@gmx.net", comment = c(ORCID = "0000-0001-6002-6980")), person(given = "Jakob", family = "Richter", role = "aut", email = "jakob1richter@gmail.com", comment = c(ORCID = "0000-0003-4481-5554")), person(given = "Xudong", family = "Sun", role = "aut", email = "smilesun.east@gmail.com", comment = c(ORCID = "0000-0003-3269-2307")), person(given = "Martin", family = "Binder", role = "aut", email = "mlr.developer@mb706.com"))
Description: Define parameter spaces, constraints and dependencies for arbitrary algorithms, to program on such spaces. Also includes statistical designs and random samplers. Objects are implemented as 'R6' classes.
License: LGPL-3
URL: https://paradox.mlr-org.com
BugReports: https://github.com/mlr-org/paradox/issues
Imports: backports, checkmate, data.table, mlr3misc, R6
Suggests: lhs, testthat
Encoding: UTF-8
NeedsCompilation: no
RoxygenNote: 6.1.1
Collate: 'Condition.R' 'Design.R' 'NoDefault.R' 'Param.R' 'ParamDbl.R' 'ParamFct.R' 'ParamInt.R' 'ParamLgl.R' 'ParamSet.R' 'ParamSetCollection.R' 'ParamUty.R' 'Sampler.R' 'Sampler1D.R' 'SamplerHierarchical.R' 'SamplerJointIndep.R' 'SamplerUnif.R' 'asserts.R' 'generate_design_grid.R' 'generate_design_lhs.R' 'generate_design_random.R' 'zzz.R'
Packaged: 2019-07-10 15:32:49 UTC; michel
Author: Michel Lang [cre, aut] (<https://orcid.org/0000-0001-9754-0393>), Bernd Bischl [aut] (<https://orcid.org/0000-0001-6002-6980>), Jakob Richter [aut] (<https://orcid.org/0000-0003-4481-5554>), Xudong Sun [aut] (<https://orcid.org/0000-0003-3269-2307>), Martin Binder [aut]
Maintainer: Michel Lang <michellang@gmail.com>
Repository: CRAN
Date/Publication: 2019-07-12 14:50:02 UTC

More information about paradox at CRAN
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New package MGDrivE with initial version 1.0.0
Package: MGDrivE
Type: Package
Title: Mosquito Gene Drive Explorer
Version: 1.0.0
Authors@R: c( person("Héctor Manuel", "Sánchez Castellanos", email = "sanchez.hmsc@berkeley.edu", role = c("aut","cre")), person("Jared", "Bennett", email = "jared_bennett@berkeley.edu ", role = "aut"), person("Sean", "Wu", email = "slwu89@berkeley.edu", role = "aut"), person("John M.", "Marshall", email = "john.marshall@berkeley.edu", role = "aut") )
Maintainer: Héctor Manuel Sánchez Castellanos <sanchez.hmsc@berkeley.edu>
URL: https://marshalllab.github.io/MGDrivE/, https://www.marshalllab.com/
BugReports: https://github.com/MarshallLab/MGDrivE/issues
Description: Provides a model designed to be a reliable testbed where various gene drive interventions for mosquito-borne diseases control. It is being developed to accommodate the use of various mosquito-specific gene drive systems within a population dynamics framework that allows migration of individuals between patches in landscape. Previous work developing the population dynamics can be found in Deredec et al. (2001) <doi:10.1073/pnas.1110717108> and Hancock & Godfray (2007) <doi:10.1186/1475-2875-6-98>, and extensions to accommodate basic CRISPR homing dynamics in Marshall et al. (2017) <doi:10.1038/s41598-017-02744-7>.
License: GPL-3
Encoding: UTF-8
Imports: R6, Rcpp, Rdpack (>= 0.7), grDevices, graphics, stats, utils
RdMacros: Rdpack
LinkingTo: Rcpp
Depends: R (>= 2.10), data.table
ByteCompile: true
LazyData: true
RoxygenNote: 6.1.1
Suggests: knitr, rmarkdown
VignetteBuilder: knitr
NeedsCompilation: yes
Packaged: 2019-07-03 19:46:03 UTC; jared
Author: Héctor Manuel Sánchez Castellanos [aut, cre], Jared Bennett [aut], Sean Wu [aut], John M. Marshall [aut]
Repository: CRAN
Date/Publication: 2019-07-12 15:00:03 UTC

More information about MGDrivE at CRAN
Permanent link

Package geometry updated to version 0.4.2 with previous version 0.4.1.1 dated 2019-07-02

Title: Mesh Generation and Surface Tessellation
Description: Makes the 'Qhull' library <http://www.qhull.org> available in R, in a similar manner as in Octave and MATLAB. Qhull computes convex hulls, Delaunay triangulations, halfspace intersections about a point, Voronoi diagrams, furthest-site Delaunay triangulations, and furthest-site Voronoi diagrams. It runs in 2D, 3D, 4D, and higher dimensions. It implements the Quickhull algorithm for computing the convex hull. Qhull does not support constrained Delaunay triangulations, or mesh generation of non-convex objects, but the package does include some R functions that allow for this.
Author: Jean-Romain Roussel [cph, ctb] (wrote tsearch function with QuadTrees), C. B. Barber [cph], Kai Habel [cph, aut], Raoul Grasman [cph, aut], Robert B. Gramacy [cph, aut], Pavlo Mozharovskyi [cph, aut], David C. Sterratt [cph, aut, cre] (<https://orcid.org/0000-0001-9092-9099>)
Maintainer: David C. Sterratt <david.c.sterratt@ed.ac.uk>

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More information about geometry at CRAN
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Package AGHmatrix updated to version 1.0.0 with previous version 0.0.5 dated 2019-03-26

Title: Relationship Matrices for Diploid and Autopolyploid Species
Description: Computation of A (pedigree), G (genomic-base), and H (A corrected by G) relationship matrices for diploid and autopolyploid species. Several methods are implemented considering additive and non-additive models.
Author: Rodrigo Amadeu [aut, cre], Catherine Cellon [ctb], Leticia Lara [ctb], Marcio Resende [ctb], Ivone Oliveira [ctb], Luis Ferrao [ctb], Patricio Munoz [ctb], Augusto Garcia [ctb]
Maintainer: Rodrigo Amadeu <rramadeu@ufl.edu>

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Package LogConcDEAD updated to version 1.6-3 with previous version 1.6-1 dated 2018-04-13

Title: Log-Concave Density Estimation in Arbitrary Dimensions
Description: Software for computing a log-concave (maximum likelihood) estimator for i.i.d. data in any number of dimensions. For a detailed description of the method see Cule, Samworth and Stewart (2010, Journal of Royal Statistical Society Series B, <doi:10.1111/j.1467-9868.2010.00753.x>).
Author: Madeleine Cule, Robert Gramacy, Richard Samworth, Yining Chen
Maintainer: Yining Chen <Y.Chen101@lse.ac.uk>

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Package ggstatsplot updated to version 0.0.12 with previous version 0.0.11 dated 2019-06-14

Title: 'ggplot2' Based Plots with Statistical Details
Description: Extension of 'ggplot2', 'ggstatsplot' creates graphics with details from statistical tests included in the plots themselves. It is targeted primarily at behavioral sciences community to provide a one-line code to generate information-rich plots for statistical analysis of continuous (violin plots, scatterplots, histograms, dot plots, dot-and-whisker plots) or categorical (pie and bar charts) data. Currently, it supports only the most common types of statistical tests: parametric, nonparametric, robust, and bayesian versions of t-test/anova, correlation analyses, contingency table analysis, and regression analyses.
Author: Indrajeet Patil [cre, aut, ctb] (<https://orcid.org/0000-0003-1995-6531>), Chuck Powell [aut, ctb] (<https://orcid.org/0000-0002-3606-2188>)
Maintainer: Indrajeet Patil <patilindrajeet.science@gmail.com>

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Package diffeqr updated to version 0.1.2 with previous version 0.1.1 dated 2018-04-27

Title: Solving Differential Equations (ODEs, SDEs, DDEs, DAEs)
Description: An interface to 'DifferentialEquations.jl' <http://docs.juliadiffeq.org/latest/> from the R programming language. It has unique high performance methods for solving ordinary differential equations (ODE), stochastic differential equations (SDE), delay differential equations (DDE), differential-algebraic equations (DAE), and more. Much of the functionality, including features like adaptive time stepping in SDEs, are unique and allow for multiple orders of magnitude speedup over more common methods. 'diffeqr' attaches an R interface onto the package, allowing seamless use of this tooling by R users.
Author: Christopher Rackauckas [aut, cre]
Maintainer: Christopher Rackauckas <me@chrisrackauckas.com>

Diff between diffeqr versions 0.1.1 dated 2018-04-27 and 0.1.2 dated 2019-07-12

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Package ClimProjDiags updated to version 0.0.4 with previous version 0.0.3 dated 2019-04-30

Title: Set of Tools to Compute Various Climate Indices
Description: Set of tools to compute metrics and indices for climate analysis. The package provides functions to compute extreme indices, evaluate the agreement between models and combine theses models into an ensemble. Multi-model time series of climate indices can be computed either after averaging the 2-D fields from different models provided they share a common grid or by combining time series computed on the model native grid. Indices can be assigned weights and/or combined to construct new indices.
Author: BSC-CNS [aut, cph], Alasdair Hunter [aut], Nuria Perez-Zanon [aut, cre], Nicolau Manubens [ctb], Louis-Philippe Caron [ctb]
Maintainer: Nuria Perez-Zanon <nuria.perez@bsc.es>

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Package vitae updated to version 0.2.0 with previous version 0.1.0 dated 2019-01-08

Title: Curriculum Vitae for R Markdown
Description: Provides templates and functions to simplify the production and maintenance of curriculum vitae.
Author: Mitchell O'Hara-Wild [aut, cre] (<https://orcid.org/0000-0001-6729-7695>), Rob Hyndman [aut] (<https://orcid.org/0000-0002-2140-5352>)
Maintainer: Mitchell O'Hara-Wild <mail@mitchelloharawild.com>

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Package Rfast updated to version 1.9.5 with previous version 1.9.4 dated 2019-05-24

Title: A Collection of Efficient and Extremely Fast R Functions
Description: A collection of fast (utility) functions for data analysis. Column- and row- wise means, medians, variances, minimums, maximums, many t, F and G-square tests, many regressions (normal, logistic, Poisson), are some of the many fast functions. Reference: Tsagris M, Papadakis M. (2018). Taking R to its limits: 70+ tips. PeerJ Preprints 6:e26605v1 <doi:10.7287/peerj.preprints.26605v1>.
Author: Manos Papadakis, Michail Tsagris, Marios Dimitriadis, Stefanos Fafalios, Ioannis Tsamardinos, Matteo Fasiolo, Giorgos Borboudakis, John Burkardt, Changliang Zou, Kleanthi Lakiotaki and Christina Chatzipantsiou.
Maintainer: Manos Papadakis <rfastofficial@gmail.com>

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More information about Rfast at CRAN
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Package DiscreteFDR updated to version 1.3 with previous version 1.2 dated 2019-01-07

Title: Multiple Testing Procedures with Adaptation for Discrete Tests
Description: Multiple testing procedures described in the paper Döhler, Durand and Roquain (2018) "New FDR bounds for discrete and heterogeneous tests" <doi:10.1214/18-EJS1441>. The main procedures of the paper (HSU and HSD), their adaptive counterparts (AHSU and AHSD), and the HBR variant are available and are coded to take as input a set of observed p-values and their discrete support under the null. A function to compute such p-values and supports for Fisher's exact tests is also provided, along with a wrapper allowing to apply discrete procedures directly from contingency tables.
Author: Sebastian Döhler [ctb], Guillermo Durand [aut, ctb], Florian Junge [aut, cre], Etienne Roquain [ctb]
Maintainer: Florian Junge <florian.junge@h-da.de>

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Permanent link

New package testextra with initial version 0.1.0
Package: testextra
Type: Package
Title: Extract Test Blocks
Version: 0.1.0
Authors@R: c( person("Andrew", "Redd", role = c("aut", "cre") , email = "andrew.redd@hsc.utah.edu" , comment = c(ORCID = "https://orcid.org/000-0002-6149-2438") ), person("R Documentation Task Force", role=c("cph") , comment = c(url = "https://rdoctaskforce.github.io/") ), person("R Consortium", role="fnd" , comment = c(url = "https://www.r-consortium.org") ))
Maintainer: Andrew Redd <andrew.redd@hsc.utah.edu>
Description: A collection of testing enhancements and utilities. Including utilities for extracting inline test blocks from package source files.
License: GPL-2
Encoding: UTF-8
Language: en-US
LazyData: true
Imports: assertthat, methods, parsetools, pkgcond, postlogic, purrr, rlang, stringi, testthat, utils
Suggests: covr, devtools, withr, rstudioapi, htmltools, shiny, yaml, DT
RoxygenNote: 6.1.1
Collate: 'extract_tests.R' 'catch_condition.R' 'inheritance.R' 'new_namespace.R' 'strings.R' 'util-testing.R' 'validity.R' 'coverage.R'
URL: https://github.com/RDocTaskForce/testextra
BugReports: https://github.com/RDocTaskForce/testextra/issues
NeedsCompilation: no
Packaged: 2019-01-11 19:40:58 UTC; u0092104
Author: Andrew Redd [aut, cre] (<https://orcid.org/000-0002-6149-2438>), R Documentation Task Force [cph] (https://rdoctaskforce.github.io/), R Consortium [fnd] (https://www.r-consortium.org)
Repository: CRAN
Date/Publication: 2019-01-18 22:30:03 UTC

More information about testextra at CRAN
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New package sinx with initial version 0.0.12
Package: sinx
Version: 0.0.12
Date: 2019-07-12
Title: Sino Xmen Said
Authors@R: c( person("Peng", "Zhao", role = c("aut", "cre"), email = "pzhao@pzhao.net") )
Maintainer: Peng Zhao <pzhao@pzhao.net>
Imports: utils, cowsay, jsonlite, xaringan, pagedown, bookdownplus, rosr, crayon, multicolor, rmsfact, clipr
License: GPL-3
Depends: R (>= 3.1.0)
Suggests: knitr, rmarkdown
Description: Displays a pseudorandom message from a database of quotations. It works as an advanced version of the package 'fortunes', while 'sinx' supports multi-byte languages such as Chinese. The databases of 'sinx' can be given in markdown format, which is easier and more friendly than spread sheets for users.
URL: https://github.com/pzhaonet/sinx
BugReports: https://github.com/pzhaonet/sinx/issues
RoxygenNote: 6.1.1
NeedsCompilation: no
LazyData: true
VignetteBuilder: knitr
Packaged: 2019-07-12 08:14:03 UTC; Peng.Zhao
Author: Peng Zhao [aut, cre]
Repository: CRAN
Date/Publication: 2019-07-12 09:12:40 UTC

More information about sinx at CRAN
Permanent link

Package rticles updated to version 0.9 with previous version 0.8 dated 2019-05-14

Title: Article Formats for R Markdown
Description: A suite of custom R Markdown formats and templates for authoring journal articles and conference submissions.
Author: JJ Allaire [aut], Yihui Xie [aut, cre] (<https://orcid.org/0000-0003-0645-5666>), R Foundation [aut, cph], Hadley Wickham [aut], Journal of Statistical Software [aut, cph], RStudio [cph], Ramnath Vaidyanathan [aut, cph], Association for Computing Machinery [aut, cph], Carl Boettiger [aut, cph], Elsevier [aut, cph], Karl Broman [aut, cph], Kirill Mueller [aut, cph], Bastiaan Quast [aut, cph], Randall Pruim [aut, cph], Ben Marwick [aut, cph], Charlotte Wickham [aut, cph], Oliver Keyes [aut, cph], Miao Yu [aut, cph], Daniel Emaasit [aut, cph], Thierry Onkelinx [aut, cph], Alessandro Gasparini [aut, cph] (<https://orcid.org/0000-0002-8319-7624>), Marc-Andre Desautels [aut, cph], Dominik Leutnant [aut, cph] (<https://orcid.org/0000-0003-3293-2315>), MDPI [aut, cph], Taylor and Francis [aut, cph], Oğuzhan Öğreden [aut] (<https://orcid.org/0000-0002-9949-3348>), Dalton Hance [aut], Daniel Nüst [aut, cph] (<https://orcid.org/0000-0002-0024-5046>), Petter Uvesten [aut, cph], Elio Campitelli [aut, cph] (<https://orcid.org/0000-0002-7742-9230>), John Muschelli [aut, cph] (<https://orcid.org/0000-0001-6469-1750>)
Maintainer: Yihui Xie <xie@yihui.name>

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 rticles-0.9/rticles/NEWS.md                                                                                   |   11 
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 rticles-0.9/rticles/README.md                                                                                 |    2 
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Package osrm updated to version 3.3.1 with previous version 3.3.0 dated 2019-04-29

Title: Interface Between R and the OpenStreetMap-Based Routing Service OSRM
Description: An interface between R and the OSRM API. OSRM is a routing service based on OpenStreetMap data. See <http://project-osrm.org/> for more information. This package allows to compute distances (travel time and kilometric distance) between points and travel time matrices.
Author: Timothée Giraud [cre, aut] (<https://orcid.org/0000-0002-1932-3323>), Robin Cura [ctb], Matthieu Viry [ctb]
Maintainer: Timothée Giraud <timothee.giraud@cnrs.fr>

Diff between osrm versions 3.3.0 dated 2019-04-29 and 3.3.1 dated 2019-07-12

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Package cricketr updated to version 0.0.22 with previous version 0.0.21 dated 2019-07-01

Title: Analyze Cricketers and Cricket Teams Based on ESPN Cricinfo Statsguru
Description: Tools for analyzing performances of cricketers based on stats in ESPN Cricinfo Statsguru. The toolset can be used for analysis of Tests,ODIs and Twenty20 matches of both batsmen and bowlers. The package can also be used to analyze team performances.
Author: Tinniam V Ganesh
Maintainer: Tinniam V Ganesh <tvganesh.85@gmail.com>

Diff between cricketr versions 0.0.21 dated 2019-07-01 and 0.0.22 dated 2019-07-12

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Package rosr updated to version 0.0.8 with previous version 0.0.7 dated 2019-05-02

Title: Create Reproducible Research Projects
Description: Creates reproducible academic projects with integrated academic elements, including datasets, references, codes, images, manuscripts, dissertations, slides and so on. These elements are well connected so that they can be easily synchronized and updated.
Author: Peng Zhao [aut, cre]
Maintainer: Peng Zhao <pzhao@pzhao.net>

Diff between rosr versions 0.0.7 dated 2019-05-02 and 0.0.8 dated 2019-07-12

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Package quint updated to version 2.0.1 with previous version 2.0.0 dated 2018-09-28

Title: Qualitative Interaction Trees
Description: Grows a qualitative interaction tree. Quint is a tool for subgroup analysis, suitable for data from a two-arm randomized controlled trial.
Author: Elise Dusseldorp [aut, cre, cph], Lisa Doove [aut], Jeanne van de Put [aut], Cor Ninaber [ctb] (supported with the plot function), Iven Van Mechelen [aut, cph], Juan Claramunt Gonzalez [aut]
Maintainer: Elise Dusseldorp <elise.dusseldorp@fsw.leidenuniv.nl>

Diff between quint versions 2.0.0 dated 2018-09-28 and 2.0.1 dated 2019-07-12

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Package DynamicGP (with last version 1.1-3) was removed from CRAN

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

2019-07-09 1.1-3

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Package xaringan updated to version 0.11 with previous version 0.10 dated 2019-05-14

Title: Presentation Ninja
Description: Create HTML5 slides with R Markdown and the JavaScript library 'remark.js' (<https://remarkjs.com>).
Author: Yihui Xie [aut, cre] (<https://orcid.org/0000-0003-0645-5666>), Benjie Gillam [ctb], Claus Thorn Ekstrøm [ctb], Daniel Anderson [ctb], Dawei Lang [ctb], Garrick Aden-Buie [ctb], John Little [ctb], Joseph Casillas [ctb], Michael Wayne Kearney [ctb], Nan-Hung Hsieh [ctb], Ole Petter Bang [ctb] (CSS in rmarkdown/templates/xaringan/resources/default.css), Patrick Schratz [ctb], Paul Lemmens [ctb], Sean Lopp [ctb], Lucy D'Agostino McGowan [ctb] (<https://orcid.org/0000-0001-7297-9359>), Emi Tanaka [ctb], Yongfu Liao [ctb], Malcolm Barrett [ctb] (<https://orcid.org/0000-0003-0299-5825>), Alessandro Gasparini [ctb] (<https://orcid.org/0000-0002-8319-7624>), Yue Jiang [ctb] (<https://orcid.org/0000-0002-9798-5517>)
Maintainer: Yihui Xie <xie@yihui.name>

Diff between xaringan versions 0.10 dated 2019-05-14 and 0.11 dated 2019-07-12

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Package rmarkdown updated to version 1.14 with previous version 1.13 dated 2019-05-22

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

Diff between rmarkdown versions 1.13 dated 2019-05-22 and 1.14 dated 2019-07-12

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