Mon, 24 Sep 2018

New package thriftr with initial version 1.0.3
Package: thriftr
Type: Package
Title: Apache Thrift Client Server
Version: 1.0.3
Date: 2018-09-16
Authors@R: c(person("Marek", "Jagielski", role = c("aut", "cre", "cph"), email = "marek.jagielski@gmail.com"), person("Lixin", "Yu", role = c("aut", "cph")))
Author: Marek Jagielski [aut, cre, cph], Lixin Yu [aut, cph]
Maintainer: Marek Jagielski <marek.jagielski@gmail.com>
Description: Pure R implementation of Apache Thrift. This library doesn't require any code generation. To learn more about Thrift go to <https://thrift.apache.org>.
License: MIT + file LICENSE
URL: https://github.com/systemincloud/thriftr
BugReports: https://github.com/systemincloud/thriftr/issues
Suggests: testthat
Encoding: UTF-8
Imports: R6, rly, stringi
RoxygenNote: 6.0.1
Collate: 'thrift.R' 'transport.R' 'rpc.R' 'parser.R' 'protocol_binary.R' 'server.R' 'transport_buffered.R' 'transport_memory.R' 'transport_socket.R' 'utils.R'
NeedsCompilation: no
Packaged: 2018-09-16 20:36:48 UTC; lupus
Repository: CRAN
Date/Publication: 2018-09-24 23:10:03 UTC

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New package splinetree with initial version 0.1.0
Package: splinetree
Title: Longitudinal Regression Trees and Forests
Version: 0.1.0
Authors@R: c(person("Anna", "Neufeld", email = "aneufeld@uw.edu", role = c("aut", "cre")), person("Brianna", "Heggeseth", email = "bheggese@macalester.edu", role = c("aut","ths")))
Description: Builds regression trees and random forests for longitudinal or functional data using a spline projection method. Implements and extends the work of Yu and Lambert (1999) <doi:10.1080/10618600.1999.10474847>. This method allows trees and forests to be built while considering either level and shape or only shape of response trajectories.
Depends: R (>= 3.5.0), rpart, nlme, splines
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
Imports: mosaic, ggplot2, treeClust, mclust
RoxygenNote: 6.1.0
Suggests: R.rsp, knitr, rmarkdown, testthat
VignetteBuilder: R.rsp
BugReports: https://github.com/anna-neufeld/splinetree/issues
URL: https://github.com/anna-neufeld/splinetree
NeedsCompilation: no
Packaged: 2018-09-16 22:02:03 UTC; annaneufeld
Author: Anna Neufeld [aut, cre], Brianna Heggeseth [aut, ths]
Maintainer: Anna Neufeld <aneufeld@uw.edu>
Repository: CRAN
Date/Publication: 2018-09-24 23:30:03 UTC

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New package PBRF with initial version 1.0.0
Package: PBRF
Type: Package
Title: The Probability of Being in Response Function and Its Variance Estimates
Version: 1.0.0
Date: 2018-09-22
Maintainer: Xiaodong Luo <xiaodong.luo@sanofi.com>
Description: Provides three ways to estimate the probability of being in response function (PBRF) The estimates are presented in Tsai, Luo and Crowley (2017) <doi: 10.1007/978-981-10-0126-0_10>.
Authors@R: c( person(given="Xiaodong", family="Luo", email = "xiaodong.luo@sanofi.com", role =c("aut", "cre")), person("Sanofi", role = "cph"))
License: GPL (>= 2)
Encoding: UTF-8
RoxygenNote: 5.0.1
LazyData: true
NeedsCompilation: yes
Packaged: 2018-09-22 13:15:48 UTC; Administrator
Author: Xiaodong Luo [aut, cre], Sanofi [cph]
Repository: CRAN
Date/Publication: 2018-09-24 23:20:02 UTC

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Package iptools updated to version 0.6.0 with previous version 0.4.0 dated 2016-04-04

Title: Manipulate, Validate and Resolve 'IP' Addresses
Description: A toolkit for manipulating, validating and testing 'IP' addresses and ranges, along with datasets relating to 'IP' addresses. Tools are also provided to map 'IPv4' blocks to country codes. While it primarily has support for the 'IPv4' address space, more extensive 'IPv6' support is intended.
Author: Bob Rudis <bob@rud.is> [aut, cre], Oliver Keyes <ironholds@gmail.com> [aut], Tim Smith [ctb]
Maintainer: Bob Rudis <bob@rud.is>

Diff between iptools versions 0.4.0 dated 2016-04-04 and 0.6.0 dated 2018-09-24

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 55 files changed, 1312 insertions(+), 355 deletions(-)

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New package hgutils with initial version 0.2.3
Package: hgutils
Version: 0.2.3
Date: 2018-09-16
Title: Collection of Utility Functions
Authors@R: person("H.G.", "van den Boorn", email = "hvdboorn@gmail.com", role = c("aut", "cre"))
Description: A handy collection of utility functions designed to aid in package development, plotting and scientific research. Package development functionalities includes among others tools such as cross-referencing package imports with the description file, analysis of redundant package imports, editing of the description file and the creation of package badges for GitHub. Some of the other functionalities include automatic package installation and loading, plotting points without overlap, creating nice breaks for plots, overview tables and many more handy utility functions.
Depends: R (>= 3.1)
Imports: crayon, grDevices, limSolve, magrittr, stringr, utils, XML
Suggests: methods, testthat
License: GPL-3
URL: https://github.com/hvdboorn/hgutils
BugReports: https://github.com/hvdboorn/hgutils/issues
Encoding: UTF-8
LazyData: true
Language: en-GB
RoxygenNote: 6.1.0
NeedsCompilation: no
Packaged: 2018-09-16 19:21:39 UTC; H.G. van den Boorn
Author: H.G. van den Boorn [aut, cre]
Maintainer: H.G. van den Boorn <hvdboorn@gmail.com>
Repository: CRAN
Date/Publication: 2018-09-24 23:10:06 UTC

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New package GNAR with initial version 0.2.7
Package: GNAR
Type: Package
Title: Methods for Fitting Network Time Series Models
Version: 0.2.7
Date: 2018-09-16
Author: Kathryn Leeming [aut], Guy Nason [aut], Matt Nunes [aut, cre], Marina Knight [ctb]
Authors@R: c(person("Kathryn", "Leeming", role="aut"), person("Guy","Nason",role="aut"), person("Matt", "Nunes", role=c("aut","cre"),email="nunesrpackages@gmail.com"), person("Marina","Knight",role="ctb"))
Maintainer: Matt Nunes <nunesrpackages@gmail.com>
Description: Simulation of, and fitting models for, Generalised Network Autoregressive (GNAR) time series models which take account of network structure. Such models are described in Knight et al. (2016), see <arXiv:1603.03221>.
Depends: igraph
License: GPL-2
Encoding: UTF-8
LazyData: true
NeedsCompilation: no
Packaged: 2018-09-16 10:19:53 UTC; matt
Repository: CRAN
Date/Publication: 2018-09-24 23:10:20 UTC

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New package behaviorchange with initial version 0.0.2
Package: behaviorchange
Type: Package
Title: Tools for Behavior Change Researchers and Professionals
Version: 0.0.2
Date: 2018-09-25
Authors@R: c(person("Gjalt-Jorn", "Peters", email = "gjalt-jorn@a-bc.eu", role = c("aut", "cre", "ctb")))
Maintainer: Gjalt-Jorn Peters <gjalt-jorn@a-bc.eu>
License: GPL (>= 3)
Description: Contains specialised analyses and visualisation tools for behavior change science. These facilitate conducting determinant studies (for example, using confidence interval-based estimation of relevance, CIBER, or CIBERlite plots) and systematically developing, reporting, and analysing interventions (for example, using acyclic behavior change diagrams). This package is especially useful for researchers in the field of behavior change or health psychology and to behavior change professionals such as intervention developers and prevention workers.
URL: https://a-bc.eu
BugReports: https://github.com/academy-of-behavior-change/behaviorchange/issues
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.0.1
Depends: R (>= 3.0.0)
Imports: data.tree (>= 0.7.5), DiagrammeR (>= 1.0.0), ggplot2 (>= 2.2.1), googlesheets (>= 0.3.0), gridExtra (>= 2.3), gtable (>= 0.2.0), magrittr (>= 0.1.5), ufs (>= 0.0.1), userfriendlyscience (>= 0.7.1), viridis (>= 0.5.1)
NeedsCompilation: no
Packaged: 2018-09-24 18:33:00 UTC; micro
Author: Gjalt-Jorn Peters [aut, cre, ctb]
Repository: CRAN
Date/Publication: 2018-09-24 23:10:16 UTC

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Package flexclust updated to version 1.4-0 with previous version 1.3-5 dated 2018-02-14

Title: Flexible Cluster Algorithms
Description: The main function kcca implements a general framework for k-centroids cluster analysis supporting arbitrary distance measures and centroid computation. Further cluster methods include hard competitive learning, neural gas, and QT clustering. There are numerous visualization methods for cluster results (neighborhood graphs, convex cluster hulls, barcharts of centroids, ...), and bootstrap methods for the analysis of cluster stability.
Author: Friedrich Leisch [aut, cre] (<https://orcid.org/0000-0001-7278-1983>), Evgenia Dimitriadou [ctb], Bettina Gruen [aut] (<https://orcid.org/0000-0001-7265-4773>)
Maintainer: Friedrich Leisch <Friedrich.Leisch@R-project.org>

Diff between flexclust versions 1.3-5 dated 2018-02-14 and 1.4-0 dated 2018-09-24

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Package frequencyConnectedness updated to version 0.2.1 with previous version 0.2.0 dated 2018-01-03

Title: Spectral Decomposition of Connectedness Measures
Description: Accompanies a paper (Barunik, Krehlik (2018) <doi:10.1093/jjfinec/nby001>) dedicated to spectral decomposition of connectedness measures and their interpretation. We implement all the developed estimators as well as the historical counterparts. For more information, see the help or GitHub page (<https://github.com/tomaskrehlik/frequencyConnectedness>) for relevant information.
Author: Tomas Krehlik [aut, cre]
Maintainer: Tomas Krehlik <tomas.krehlik@gmail.com>

Diff between frequencyConnectedness versions 0.2.0 dated 2018-01-03 and 0.2.1 dated 2018-09-24

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Package smapr updated to version 0.2.0 with previous version 0.1.2 dated 2018-06-19

Title: Acquisition and Processing of NASA Soil Moisture Active-Passive (SMAP) Data
Description: Facilitates programmatic access to NASA Soil Moisture Active Passive (SMAP) data with R. It includes functions to search for, acquire, and extract SMAP data.
Author: Maxwell Joseph [aut, cre], Matthew Oakley [aut], Zachary Schira [aut]
Maintainer: Maxwell Joseph <maxwell.b.joseph@colorado.edu>

Diff between smapr versions 0.1.2 dated 2018-06-19 and 0.2.0 dated 2018-09-24

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Package PWFSLSmoke updated to version 1.0.33 with previous version 1.0.20 dated 2018-05-08

Title: Utilities for Working with Air Quality Monitoring Data
Description: Utilities for working with air quality monitoring data with a focus on small particulates (PM2.5) generated by wildfire smoke. Functions are provided for downloading available data from the United States 'EPA' <https://www.epa.gov/outdoor-air-quality-data> and it's 'AirNow' air quality site <https://www.airnow.gov>. Additional sources of PM2.5 data made accessible by the package include: 'AIRSIS' (password protected) <https://www.oceaneering.com/data-management/> and 'WRCC' <https://wrcc.dri.edu/cgi-bin/smoke.pl>. Data compilations are provided by 'PWFSL' <https://www.fs.fed.us/pnw/pwfsl/>.
Author: Jonathan Callahan [aut, cre], Rohan Aras [aut], Zach Dingels [aut], Jon Hagg [aut], Jimin Kim [aut], Helen Miller [aut], Spencer Pease [aut], Rex Thompson [aut], Alice Yang [aut]
Maintainer: Jonathan Callahan <jonathan.s.callahan@gmail.com>

Diff between PWFSLSmoke versions 1.0.20 dated 2018-05-08 and 1.0.33 dated 2018-09-24

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More information about PWFSLSmoke at CRAN
Permanent link

Package aqp updated to version 1.16-3 with previous version 1.16 dated 2018-04-12

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

Diff between aqp versions 1.16 dated 2018-04-12 and 1.16-3 dated 2018-09-24

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Package pROC updated to version 1.13.0 with previous version 1.12.1 dated 2018-05-06

Title: Display and Analyze ROC Curves
Description: Tools for visualizing, smoothing and comparing receiver operating characteristic (ROC curves). (Partial) area under the curve (AUC) can be compared with statistical tests based on U-statistics or bootstrap. Confidence intervals can be computed for (p)AUC or ROC curves.
Author: Xavier Robin [cre, aut] (<https://orcid.org/0000-0002-6813-3200>), Natacha Turck [aut], Alexandre Hainard [aut], Natalia Tiberti [aut], Frédérique Lisacek [aut], Jean-Charles Sanchez [aut], Markus Müller [aut], Stefan Siegert [ctb] (Fast DeLong code)
Maintainer: Xavier Robin <pROC-cran@xavier.robin.name>

Diff between pROC versions 1.12.1 dated 2018-05-06 and 1.13.0 dated 2018-09-24

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Package parallelDist updated to version 0.2.2 with previous version 0.2.1 dated 2017-12-04

Title: Parallel Distance Matrix Computation using Multiple Threads
Description: A fast parallelized alternative to R's native 'dist' function to calculate distance matrices for continuous, binary, and multi-dimensional input matrices, which supports a broad variety of 39 predefined distance functions from the 'stats', 'proxy' and 'dtw' R packages, as well as user- defined functions written in C++. For ease of use, the 'parDist' function extends the signature of the 'dist' function and uses the same parameter naming conventions as distance methods of existing R packages. The package is mainly implemented in C++ and leverages the 'RcppParallel' package to parallelize the distance computations with the help of the 'TinyThread' library. Furthermore, the 'Armadillo' linear algebra library is used for optimized matrix operations during distance calculations. The curiously recurring template pattern (CRTP) technique is applied to avoid virtual functions, which improves the Dynamic Time Warping calculations while the implementation stays flexible enough to support different DTW step patterns and normalization methods.
Author: Alexander Eckert [aut, cre]
Maintainer: Alexander Eckert <info@alexandereckert.com>

Diff between parallelDist versions 0.2.1 dated 2017-12-04 and 0.2.2 dated 2018-09-24

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More information about parallelDist at CRAN
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Package doParallel updated to version 1.0.14 with previous version 1.0.11 dated 2017-09-28

Title: Foreach Parallel Adaptor for the 'parallel' Package
Description: Provides a parallel backend for the %dopar% function using the parallel package.
Author: Rich Calaway [cre], Microsoft Corporation [aut, cph], Steve Weston [aut], Dan Tenenbaum [ctb]
Maintainer: Rich Calaway <richcala@microsoft.com>

Diff between doParallel versions 1.0.11 dated 2017-09-28 and 1.0.14 dated 2018-09-24

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More information about doParallel at CRAN
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Package clpAPI updated to version 1.2.9 with previous version 1.2.7 dated 2016-04-19

Title: R Interface to C API of COIN-OR Clp
Description: R Interface to C API of COIN-OR Clp, depends on COIN-OR Clp Version >= 1.12.0.
Author: Mayo Roettger [cre], Gabriel Gelius-Dietrich [aut], C. Jonathan Fritzemeier [ctb]
Maintainer: Mayo Roettger <mayo.roettger@hhu.de>

Diff between clpAPI versions 1.2.7 dated 2016-04-19 and 1.2.9 dated 2018-09-24

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More information about clpAPI at CRAN
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New package userfriendlyscience with initial version 0.7.2
Package: userfriendlyscience
Type: Package
Title: Quantitative Analysis Made Accessible
Version: 0.7.2
Date: 2018-09-25
Authors@R: c(person("Gjalt-Jorn", "Peters", email = "gjalt-jorn@userfriendlyscience.com", role = c("aut", "cre", "ctb")), person("Peter", "Verboon", role = c("ctb")), person("James", "Green", role = c("ctb")))
Maintainer: Gjalt-Jorn Peters <gjalt-jorn@userfriendlyscience.com>
License: GPL (>= 3)
Description: Contains a number of functions that serve two goals. First, to make R more accessible to people migrating from SPSS by adding a number of functions that behave roughly like their SPSS equivalents (also see <https://rosettastats.com>). Second, to make a number of slightly more advanced functions more user friendly to relatively novice users. The package also conveniently houses a number of additional functions that are intended to increase the quality of methodology and statistics in psychology, not by offering technical solutions, but by shifting perspectives, for example towards reasoning based on sampling distributions as opposed to on point estimates.
URL: http://userfriendlyscience.com
BugReports: https://github.com/matherion/userfriendlyscience/issues
LazyData: true
Imports: BiasedUrn, car, data.tree, DiagrammeR, diptest, digest, GGally, ggplot2, ggrepel, ggridges, gridExtra, GPArotation, gtable, knitr, lavaan, lme4, MASS, MBESS, minpack.lm, pander, plyr, psych, pwr, RColorBrewer, rio, scales, SCRT, SuppDists, ufs (>= 0.0.1), viridis, XML, xtable
Suggests: multcompView
NeedsCompilation: no
Packaged: 2018-09-24 16:50:22 UTC; micro
Author: Gjalt-Jorn Peters [aut, cre, ctb], Peter Verboon [ctb], James Green [ctb]
Repository: CRAN
Date/Publication: 2018-09-24 18:30:03 UTC

More information about userfriendlyscience at CRAN
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Package revengc updated to version 1.0.3 with previous version 1.0.2 dated 2018-07-18

Title: Reverse Engineering Summarized Data
Description: Decoupled (e.g. separate averages) and censored (e.g. > 100 species) variables are continually reported by many well-established organizations (e.g. World Health Organization (WHO), Centers for Disease Control and Prevention (CDC), World Bank, and various national censuses). The challenge therefore is to infer what the original data could have been given summarized information. We present an R package that reverse engineers decoupled and/or censored count data with two main functions. The cnbinom.pars() function estimates the average and dispersion parameter of a censored univariate frequency table. The rec() function reverse engineers summarized data into an uncensored bivariate table of probabilities.
Author: Samantha Duchscherer [aut, cre], UT-Battelle, LLC [cph]
Maintainer: Samantha Duchscherer <sam.duchscherer@gmail.com>

Diff between revengc versions 1.0.2 dated 2018-07-18 and 1.0.3 dated 2018-09-24

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Package live updated to version 1.5.8 with previous version 1.5.7 dated 2018-06-03

Title: Local Interpretable (Model-Agnostic) Visual Explanations
Description: Interpretability of complex machine learning models is a growing concern. This package helps to understand key factors that drive the decision made by complicated predictive model (so called black box model). This is achieved through local approximations that are either based on additive regression like model or CART like model that allows for higher interactions. The methodology is based on Tulio Ribeiro, Singh, Guestrin (2016) <doi:10.1145/2939672.2939778>. More details can be found in Staniak, Biecek (2018) <arXiv:1804.01955>.
Author: Mateusz Staniak [cre, aut], Przemysław Biecek [aut]
Maintainer: Mateusz Staniak <mateusz.staniak@math.uni.wroc.pl>

Diff between live versions 1.5.7 dated 2018-06-03 and 1.5.8 dated 2018-09-24

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Package dynr updated to version 0.1.13-4 with previous version 0.1.13-3 dated 2018-09-16

Title: Dynamic Modeling in R
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.
Author: Lu Ou [aut], Michael D. Hunter [aut, cre], Sy-Miin Chow [aut]
Maintainer: Michael D. Hunter <mhunter.ou@gmail.com>

Diff between dynr versions 0.1.13-3 dated 2018-09-16 and 0.1.13-4 dated 2018-09-24

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Package distdichoR updated to version 0.1-1 with previous version 0.1-0 dated 2018-09-19

Title: Distributional Method for the Dichotomisation of Continuous Outcomes
Description: Contains a range of functions covering the present development of the distributional method for the dichotomisation of continuous outcomes. The method provides estimates with standard error of a comparison of proportions (difference, odds ratio and risk ratio) derived, with similar precision, from a comparison of means. See the URL below or <arXiv:1809.03279> for more information.
Author: Odile Sauzet
Maintainer: Odile Sauzet <odile.sauzet@uni-bielefeld.de>

Diff between distdichoR versions 0.1-0 dated 2018-09-19 and 0.1-1 dated 2018-09-24

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Package data.tree updated to version 0.7.8 with previous version 0.7.7 dated 2018-09-23

Title: General Purpose Hierarchical Data Structure
Description: Create tree structures from hierarchical data, and traverse the tree in various orders. Aggregate, cumulate, print, plot, convert to and from data.frame and more. Useful for decision trees, machine learning, finance, conversion from and to JSON, and many other applications.
Author: Chris Hammil [ctb] (improve getting), Facundo Munoz [ctb] (improve list conversion), Markus Wamser [ctb] (fixed some typos), Pierre Formont [ctb] (additional features), Kent Russel [ctb] (documentation), Noam Ross [ctb] (fixes), Duncan Garmonsway [ctb] (fixes), Christoph Glur [aut, cre] (R interface)
Maintainer: Christoph Glur <christoph.glur@ipub.com>

Diff between data.tree versions 0.7.7 dated 2018-09-23 and 0.7.8 dated 2018-09-24

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Package cgraph updated to version 2.0.3 with previous version 2.0.2 dated 2018-08-19

Title: Computational Graphs
Description: Allows to create, evaluate, and differentiate computational graphs in R. A computational graph is a graph representation of a multivariate function decomposed by its (elementary) operations. Nodes in the graph represent arrays while edges represent dependencies among the arrays. An advantage of expressing a function as a computational graph is that this enables to differentiate the function by automatic differentiation. The 'cgraph' package supports various functions including basic arithmetic, trigonometry functions, and linear algebra functions. It differentiates computational graphs by reverse automatic differentiation. The flexible architecture of the package makes it applicable to solve a variety of problems including local sensitivity analysis, gradient-based optimization, and machine learning.
Author: Ron Triepels
Maintainer: Ron Triepels <dev@cgraph.org>

Diff between cgraph versions 2.0.2 dated 2018-08-19 and 2.0.3 dated 2018-09-24

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Package grf updated to version 0.10.1 with previous version 0.10.0 dated 2018-05-09

Title: Generalized Random Forests (Beta)
Description: A pluggable package for forest-based statistical estimation and inference. GRF currently provides methods for non-parametric least-squares regression, quantile regression, and treatment effect estimation (optionally using instrumental variables). This package is currently in beta, and we expect to make continual improvements to its performance and usability.
Author: Julie Tibshirani [aut, cre], Susan Athey [aut], Stefan Wager [aut], Rina Friedberg [ctb], Luke Miner [ctb], Marvin Wright [ctb]
Maintainer: Julie Tibshirani <jtibs@cs.stanford.edu>

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Package FENmlm updated to version 2.2.2 with previous version 2.2.1 dated 2018-09-15

Title: Fixed Effects Nonlinear Maximum Likelihood Models
Description: Efficient estimation of multiple fixed-effects maximum likelihood models with, possibly, non-linear in parameters right hand sides. Standard-errors can easily be clustered and estimations exported.
Author: Laurent Berge [aut, cre]
Maintainer: Laurent Berge <laurent.berge@uni.lu>

Diff between FENmlm versions 2.2.1 dated 2018-09-15 and 2.2.2 dated 2018-09-24

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Package checkLuhn updated to version 1.1.0 with previous version 1.0.2 dated 2018-09-03

Title: Checks if a Number is Valid Using the Luhn Algorithm
Description: Confirms if the number is Luhn compliant. Can check if credit card, IMEI number or any other Luhn based number is correct. For more info see: <https://en.wikipedia.org/wiki/Luhn_algorithm>.
Author: Adam Deacon [aut, cre], Karina Marks [ctb], Owen Jones [ctb]
Maintainer: Adam Deacon <adam@deaconsworld.org.uk>

Diff between checkLuhn versions 1.0.2 dated 2018-09-03 and 1.1.0 dated 2018-09-24

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Package CSESA updated to version 1.1.0 with previous version 1.0.4 dated 2018-06-15

Title: CRISPR-Based Salmonella Enterica Serotype Analyzer
Description: Salmonella enterica is a major cause of bacterial food-borne disease worldwide. Serotype identification is the most commonly used typing method to characterize Salmonella isolates. However, experimental serotyping needs great cost on manpower and resources. Recently, we found that the newly incorporated spacer in the clustered regularly interspaced short palindromic repeat (CRISPR) could serve as an effective marker for typing of Salmonella. It was further revealed by Li et. al (2014) <doi:10.1128/JCM.00696-14> that recognized types based on the combination of two newly incorporated spacer in both CRISPR loci showed high accordance with serotypes. Here, we developed an R package 'CSESA' to predict the serotype based on this finding. Considering it’s time saving and of high accuracy, we recommend to predict the serotypes of unknown Salmonella isolates using 'CSESA' before doing the traditional serotyping.
Author: Xia Zhang [aut, cre], Lang Yang [aut]
Maintainer: Xia Zhang <zhangxia9403@gmail.com>

Diff between CSESA versions 1.0.4 dated 2018-06-15 and 1.1.0 dated 2018-09-24

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Package WeMix updated to version 2.1.0 with previous version 2.0.0 dated 2018-08-14

Title: Weighted Mixed-Effects Models, using Multilevel Pseudo Maximum Likelihood Estimation
Description: Run mixed-effects models that include weights at every level. The WeMix package fits a Weighted Mixed model, also known as a multilevel, mixed, or hierarchical linear model (HLM). The weights could be inverse selection probabilities, such as those developed for an education survey where schools are sampled probabilistically, and then students inside of those schools are sampled probabilistically. Although mixed-effects models are already available in R, WeMix is unique in implementing methods for mixed models using weights at multiple levels. The model is fit using adaptive quadrature.
Author: Paul Bailey, Claire Kelley, Trang Nguyen, Huade Huo.
Maintainer: Claire Kelley <ckelley@air.org>

Diff between WeMix versions 2.0.0 dated 2018-08-14 and 2.1.0 dated 2018-09-24

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Package Ckmeans.1d.dp updated to version 4.2.2 with previous version 4.2.1 dated 2017-07-09

Title: Optimal and Fast Univariate Clustering
Description: Fast optimal univariate clustering and segementation by dynamic programming. Three types of problem including univariate k-means, k-median, and k-segments are solved with guaranteed optimality and reproducibility. The core algorithm minimizes the sum of within-cluster distances using respective metrics. Its advantage over heuristic clustering algorithms in efficiency and accuracy is increasingly pronounced as the number of clusters k increases. Weighted k-means and unweighted k-segments algorithms can also optimally segment time series and perform peak calling. An auxiliary function generates histograms that are adaptive to patterns in data. In contrast to heuristic methods, this package provides a powerful set of tools for univariate data analysis with guaranteed optimality. Use four spaces when indenting paragraphs within the Description.
Author: Joe Song [aut, cre], Haizhou Wang [aut]
Maintainer: Joe Song <joemsong@cs.nmsu.edu>

Diff between Ckmeans.1d.dp versions 4.2.1 dated 2017-07-09 and 4.2.2 dated 2018-09-24

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Package bigdatadist updated to version 1.1 with previous version 1.0 dated 2018-07-02

Title: Distances for Machine Learning and Statistics in the Context of Big Data
Description: Functions to compute distances between probability measures or any other data object than can be posed in this way, entropy measures for samples of curves, distances and depth measures for functional data, and the Generalized Mahalanobis Kernel distance for high dimensional data. For further details about the metrics please refer to Martos et al (2014) <doi:10.3233/IDA-140706>; Martos et al (2018) <doi:10.3390/e20010033>; Hernandez et al (2018, submitted); Martos et al (2018, submitted).
Author: Gabriel Martos [aut, cre], Nicolas Hernandez [aut]
Maintainer: Gabriel Martos <gmartos@utdt.edu>

Diff between bigdatadist versions 1.0 dated 2018-07-02 and 1.1 dated 2018-09-24

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Package BAwiR updated to version 1.1.3 with previous version 1.1.2 dated 2018-09-10

Title: Analysis of Basketball Data
Description: Collection of tools to work with basketball data. Functions available are related to friendly web scraping and visualization. Data were obtained from <http://www.euroleague.net/>, <http://www.eurocupbasketball.com/> and <http://www.acb.com>, following the instructions of their respectives robots.txt files. Tools for visualization include a population pyramid, 2D plots of archetypoids and the rest of players, percentile circular plots, plots to analyze monthly evolution, heatmaps, shooting barplots, four factor plots and maps of players' nationalities.
Author: Guillermo Vinue
Maintainer: Guillermo Vinue <Guillermo.Vinue@uv.es>

Diff between BAwiR versions 1.1.2 dated 2018-09-10 and 1.1.3 dated 2018-09-24

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Package EcoHydRology updated to version 0.4.12.1 with previous version 0.4.12 dated 2014-04-04

Title: A Community Modeling Foundation for Eco-Hydrology
Description: Provides a flexible foundation for scientists, engineers, and policy makers to base teaching exercises as well as for more applied use to model complex eco-hydrological interactions.
Author: Fuka DR, Walter MT, Archibald JA, Steenhuis TS, and Easton ZM
Maintainer: Daniel Fuka <drf28@cornell.edu>

Diff between EcoHydRology versions 0.4.12 dated 2014-04-04 and 0.4.12.1 dated 2018-09-24

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Package trackeR updated to version 1.1 with previous version 1.0.0 dated 2017-11-27

Title: Infrastructure for Running, Cycling and Swimming Data from GPS-Enabled Tracking Devices
Description: Provides infrastructure for handling running, cycling and swimming data from GPS-enabled tracking devices within R. The package provides methods to extract, clean and organise workout and competition data into session-based and unit-aware data objects of class 'trackeRdata' (S3 class). The information can then be visualised, summarised, and analysed through flexible and extensible methods. Frick and Kosmidis (2017) <doi: 10.18637/jss.v082.i07>, which is updated and maintained as one of the vignettes, provides detailed descriptions of the package and its methods, and real-data demonstrations of the package functionality.
Author: Ioannis Kosmidis [aut, cre] (<https://orcid.org/0000-0003-1556-0302>), Hannah Frick [aut] (<https://orcid.org/0000-0002-6049-5258>), Robin Hornak [aut]
Maintainer: Ioannis Kosmidis <ioannis.kosmidis@warwick.ac.uk>

Diff between trackeR versions 1.0.0 dated 2017-11-27 and 1.1 dated 2018-09-24

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More information about trackeR at CRAN
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Package semTools updated to version 0.5-1 with previous version 0.5-0 dated 2018-06-27

Title: Useful Tools for Structural Equation Modeling
Description: Provides useful tools for structural equation modeling.
Author: Terrence D. Jorgensen [aut, cre] (<https://orcid.org/0000-0001-5111-6773>), Sunthud Pornprasertmanit [aut], Alexander Schoemann [aut], Yves Rosseel [aut], Patrick Miller [ctb], Corbin Quick [ctb], Mauricio Garnier-Villarreal [ctb], James Selig [ctb], Aaron Boulton [ctb], Kristopher Preacher [ctb], Donna Coffman [ctb], Mijke Rhemtulla [ctb], Alexander Robitzsch [ctb], Craig Enders [ctb], Ruber Arslan [ctb], Bell Clinton [ctb], Pavel Panko [ctb], Edgar Merkle [ctb], Steven Chesnut [ctb], Jarrett Byrnes [ctb], Jason D. Rights [ctb], Ylenio Longo [ctb], Maxwell Mansolf [ctb]
Maintainer: Terrence D. Jorgensen <TJorgensen314@gmail.com>

Diff between semTools versions 0.5-0 dated 2018-06-27 and 0.5-1 dated 2018-09-24

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Package FishResp updated to version 1.0.0 with previous version 0.4.0 dated 2018-08-27

Title: Analytical Tool for Aquatic Respirometry
Description: Calculates metabolic rate of fish and other aquatic organisms measured using an intermittent-flow respirometry approach. The tool is used to run a set of graphical QC tests of raw respirometry data, correct it for background respiration and chamber effect, filter and extract target values of absolute and mass-specific metabolic rate. Experimental design should include background respiration tests and measuring of one or more metabolic rate traits. The package allows a user to import raw respirometry data obtained from 'AquaResp' (free software), 'AutoResp' ('LoligoSystems'), 'OxyView' ('PreSens'), 'Pyro Oxygen Logger' ('PyroScience') and 'Q-box Aqua' ('QubitSystems').
Author: Sergey Morozov [aut, cre], R.J. Scott McCairns [aut, ths], Federico Calboli [ctb], Juha Merila [ths], Stephen White [dtc], Daniel Montgomery [dtc], Laura Almodovar-Acevedo [dtc], Niclas Kolm [dtc], Alexander Kotrschal [dtc]
Maintainer: Sergey Morozov <sergey.morozov@helsinki.fi>

Diff between FishResp versions 0.4.0 dated 2018-08-27 and 1.0.0 dated 2018-09-24

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Package ffbase updated to version 0.12.5 with previous version 0.12.3 dated 2016-03-22

Title: Basic Statistical Functions for Package 'ff'
Description: Extends the out of memory vectors of 'ff' with statistical functions and other utilities to ease their usage.
Author: Edwin de Jonge, Jan Wijffels, Jan van der Laan
Maintainer: Edwin de Jonge <edwindjonge@gmail.com>

Diff between ffbase versions 0.12.3 dated 2016-03-22 and 0.12.5 dated 2018-09-24

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Package Infusion updated to version 1.3.0 with previous version 1.2.0 dated 2018-04-04

Title: Inference Using Simulation
Description: Implements functions for simulation-based inference. In particular, implements functions to perform likelihood inference from data summaries whose distributions are simulated (Rousset et al. 2017 <doi:10.1111/1755-0998.12627>).
Author: François Rousset [aut, cre, cph] (<https://orcid.org/0000-0003-4670-0371>)
Maintainer: François Rousset <francois.rousset@umontpellier.fr>

Diff between Infusion versions 1.2.0 dated 2018-04-04 and 1.3.0 dated 2018-09-24

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Package ijtiff updated to version 1.4.1 with previous version 1.4.0 dated 2018-09-10

Title: Comprehensive TIFF I/O with Full Support for 'ImageJ' TIFF Files
Description: General purpose TIFF file I/O for R users. Currently the only such package with read and write support for TIFF files with floating point (real-numbered) pixels, and the only package that can correctly import TIFF files that were saved from 'ImageJ' and write TIFF files than can be correctly read by 'ImageJ' <https://imagej.nih.gov/ij/>. Also supports text image I/O.
Author: Rory Nolan [aut, cre] (<https://orcid.org/0000-0002-5239-4043>), Kent Johnson [aut], Simon Urbanek [ctb], Sergi Padilla-Parra [ths] (<https://orcid.org/0000-0002-8010-9481>), Jeroen Ooms [rev, ctb] (<https://orcid.org/0000-0002-4035-0289>), Jon Clayden [rev] (<https://orcid.org/0000-0002-6608-0619>)
Maintainer: Rory Nolan <rorynoolan@gmail.com>

Diff between ijtiff versions 1.4.0 dated 2018-09-10 and 1.4.1 dated 2018-09-24

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

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

2017-04-18 0.2.0
2016-11-06 0.1.2
2016-03-08 0.1.1
2016-01-26 0.1.0
2016-01-04 0.0.2

Permanent link
Package IRdisplay updated to version 0.6 with previous version 0.5.0 dated 2018-05-17

Title: 'Jupyter' Display Machinery
Description: An interface to the rich display capabilities of 'Jupyter' front-ends (e.g. 'Jupyter Notebook') <https://jupyter.org>. Designed to be used from a running 'IRkernel' session <https://irkernel.github.io>.
Author: Thomas Kluyver [aut, cph], Philipp Angerer [aut, cph, cre], Jan Schulz [aut, cph]
Maintainer: Philipp Angerer <phil.angerer@gmail.com>

Diff between IRdisplay versions 0.5.0 dated 2018-05-17 and 0.6 dated 2018-09-24

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Package ape updated to version 5.2 with previous version 5.1 dated 2018-04-04

Title: Analyses of Phylogenetics and Evolution
Description: Functions for reading, writing, plotting, and manipulating phylogenetic trees, analyses of comparative data in a phylogenetic framework, ancestral character analyses, analyses of diversification and macroevolution, computing distances from DNA sequences, reading and writing nucleotide sequences as well as importing from BioConductor, and several tools such as Mantel's test, generalized skyline plots, graphical exploration of phylogenetic data (alex, trex, kronoviz), estimation of absolute evolutionary rates and clock-like trees using mean path lengths and penalized likelihood, dating trees with non-contemporaneous sequences, translating DNA into AA sequences, and assessing sequence alignments. Phylogeny estimation can be done with the NJ, BIONJ, ME, MVR, SDM, and triangle methods, and several methods handling incomplete distance matrices (NJ*, BIONJ*, MVR*, and the corresponding triangle method). Some functions call external applications (PhyML, Clustal, T-Coffee, Muscle) whose results are returned into R.
Author: Emmanuel Paradis [aut, cre, cph] (<https://orcid.org/0000-0003-3092-2199>), Simon Blomberg [aut, cph] (<https://orcid.org/0000-0003-1062-0839>), Ben Bolker [aut, cph] (<https://orcid.org/0000-0002-2127-0443>), Joseph Brown [aut, cph], Julien Claude [aut, cph], Hoa Sien Cuong [aut, cph], Richard Desper [aut, cph], Gilles Didier [aut, cph], Benoit Durand [aut, cph], Julien Dutheil [aut, cph], RJ Ewing [aut, cph], Olivier Gascuel [aut, cph], Thomas Guillerme [aut, cph], Christoph Heibl [aut, cph], Anthony Ives [aut, cph], Bradley Jones [aut, cph], Franz Krah [aut, cph], Daniel Lawson [aut, cph], Vincent Lefort [aut, cph], Pierre Legendre [aut, cph] (<https://orcid.org/0000-0002-3838-3305>), Jim Lemon [aut, cph], Eric Marcon [aut, cph], Rosemary McCloskey [aut, cph], Johan Nylander [aut, cph], Rainer Opgen-Rhein [aut, cph], Andrei-Alin Popescu [aut, cph], Manuela Royer-Carenzi [aut, cph], Klaus Schliep [aut, cph], Korbinian Strimmer [aut, cph], Damien de Vienne [aut, cph]
Maintainer: Emmanuel Paradis <Emmanuel.Paradis@ird.fr>

Diff between ape versions 5.1 dated 2018-04-04 and 5.2 dated 2018-09-24

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Package ITRSelect updated to version 1.0-1 with previous version 1.0 dated 2018-04-30

Title: Variable Selection for Optimal Individualized Dynamic Treatment Regime
Description: Sequential advantage selection (SAS, Fan, Lu and Song, 2016) <arXiv:1405.5239> and penalized A-learning (PAL, Shi, et al., 2018) methods are implement for selecting important variables involved in optimal individualized (dynamic) treatment regime in both single-stage or multi-stage studies.
Author: Chengchun Shi, Ailin Fan, Rui Song and Wenbin Lu
Maintainer: Chengchun Shi <cshi4@ncsu.edu>

Diff between ITRSelect versions 1.0 dated 2018-04-30 and 1.0-1 dated 2018-09-24

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Package afex updated to version 0.22-1 with previous version 0.21-2 dated 2018-06-24

Title: Analysis of Factorial Experiments
Description: Convenience functions for analyzing factorial experiments using ANOVA or mixed models. aov_ez(), aov_car(), and aov_4() allow specification of between, within (i.e., repeated-measures), or mixed (i.e., split-plot) ANOVAs for data in long format (i.e., one observation per row), automatically aggregating multiple observations per individual and cell of the design. mixed() fits mixed models using lme4::lmer() and computes p-values for all fixed effects using either Kenward-Roger or Satterthwaite approximation for degrees of freedom (LMM only), parametric bootstrap (LMMs and GLMMs), or likelihood ratio tests (LMMs and GLMMs). afex_plot() provides a high-level interface for interaction or one-way plots using ggplot2, combining raw data and model estimates. afex uses type 3 sums of squares as default (imitating commercial statistical software).
Author: Henrik Singmann [aut, cre] (<https://orcid.org/0000-0002-4842-3657>), Ben Bolker [aut], Jake Westfall [aut], Frederik Aust [aut] (<https://orcid.org/0000-0003-4900-788X>), Søren Højsgaard [ctb], John Fox [ctb], Michael A. Lawrence [ctb], Ulf Mertens [ctb], Jonathon Love [ctb], Russell Lenth [ctb], Rune Haubo Bojesen Christensen [ctb]
Maintainer: Henrik Singmann <singmann+afex@gmail.com>

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