Fri, 14 Sep 2018

New package rym with initial version 0.4.0
Package: rym
Type: Package
Title: R Interface to Yandex Metrika API
Version: 0.4.0
Date: 2018-09-03
Author: Alexey Seleznev <selesnow@gmail.com>
Maintainer: Alexey Seleznev <selesnow@gmail.com>
Description: Allows work with 'Management API' for load counters, segments, filters, user permissions and goals list from Yandex Metrika, 'Reporting API' allows you to get information about the statistics of site visits and other data without using the web interface, 'Logs API' allows to receive non-aggregated data and 'Compatible with Google Analytics Core Reporting API v3' allows receive information about site traffic and other data using field names from Google Analytics Core API. For more information see official documents <https://tech.yandex.ru/metrika/doc/api2/concept/about-docpage/>.
Depends: R (>= 3.5.0)
BugReports: https://github.com/selesnow/rym/issues
License: GPL-2
Imports: httr, stringr, utils
URL: http://selesnow.github.io/
Encoding: UTF-8
NeedsCompilation: no
Packaged: 2018-09-10 12:29:06 UTC; Alsey
Repository: CRAN
Date/Publication: 2018-09-14 23:00:02 UTC

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Package pimeta updated to version 1.1.1 with previous version 1.1.0 dated 2018-09-14

Title: Prediction Intervals for Random-Effects Meta-Analysis
Description: An implementation of prediction intervals for random-effects meta-analysis: Higgins et al. (2009) <doi:10.1111/j.1467-985X.2008.00552.x>, Partlett and Riley (2017) <doi:10.1002/sim.7140>, and Nagashima et al. (2018) <doi:10.1177/0962280218773520>, <arXiv:1804.01054>.
Author: Kengo Nagashima [aut, cre] (<https://orcid.org/0000-0003-4529-9045>), Hisashi Noma [aut], Toshi A. Furukawa [aut]
Maintainer: Kengo Nagashima <nshi1201@gmail.com>

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New package episcan with initial version 0.0.1
Package: episcan
Title: Scan Pairwise Epistasis
Version: 0.0.1
Author: Beibei Jiang <beibei_jiang@psych.mpg.de> and Benno Pütz <puetz@psych.mpg.de>
Maintainer: Beibei Jiang <beibei_jiang@psych.mpg.de>
Description: Searching genomic interactions with linear/logistic regression in a high-dimensional dataset is a time-consuming task. This package provides some efficient ways to scan epistasis in genome-wide interaction studies (GWIS). Both case-control status (binary outcome) and quantitative phenotype (continuous outcome) are supported (the main references: 1. Kam-Thong, T., D. Czamara, K. Tsuda, K. Borgwardt, C. M. Lewis, A. Erhardt-Lehmann, B. Hemmer, et al. (2011). <doi:10.1038/ejhg.2010.196>. 2. Kam-Thong, T., B. Pütz, N. Karbalai, B. Müller-Myhsok, and K. Borgwardt. (2011). <doi:10.1093/bioinformatics/btr218>.)
Depends: R (>= 3.5.0)
License: GPL (>= 2)
Encoding: UTF-8
Suggests: testthat, knitr, rmarkdown
VignetteBuilder: knitr
LazyData: true
RoxygenNote: 6.1.0
NeedsCompilation: no
Packaged: 2018-09-10 12:13:44 UTC; beibei_jiang
Repository: CRAN
Date/Publication: 2018-09-14 23:02:19 UTC

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New package embed with initial version 0.0.1
Package: embed
Version: 0.0.1
Title: Extra Recipes for Encoding Categorical Predictors
Description: Factor 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.
Authors@R: c( person("Max", "Kuhn", , "max@rstudio.com", c("aut", "cre")), person("RStudio", role = "cph"))
Depends: R (>= 3.1), recipes (>= 0.1.3)
Imports: rstanarm, keras, stats, dplyr, purrr, rlang, utils, broom, tidyr, tibble, lme4, tensorflow
Suggests: testthat, knitr, rmarkdown, covr
License: GPL-2
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.0.1
ByteCompile: true
URL: https://tidymodels.github.io/embed
BugReports: https://github.com/tidymodels/embed/issues
NeedsCompilation: no
Packaged: 2018-09-06 01:25:20 UTC; max
Author: Max Kuhn [aut, cre], RStudio [cph]
Maintainer: Max Kuhn <max@rstudio.com>
Repository: CRAN
Date/Publication: 2018-09-14 23:12:24 UTC

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New package cglasso with initial version 1.0.0
Package: cglasso
Version: 1.0.0
Date: 2018-09-09
Type: Package
Title: L1-Penalized Censored Gaussian Graphical Models
Author: Luigi Augugliaro
Maintainer: Luigi Augugliaro <luigi.augugliaro@unipa.it>
Depends: R (>= 3.5), igraph
Description: The l1-penalized censored Gaussian graphical model (cglasso) is an extension of the graphical lasso estimator developed to handle datasets with censored observations. An EM-like algorithm is implemented to estimate the parameters of the censored Gaussian graphical models.
Imports: methods, MASS
License: GPL (>= 2)
LazyLoad: yes
NeedsCompilation: yes
Repository: CRAN
Packaged: 2018-09-10 12:32:39 UTC; augugliaro
Date/Publication: 2018-09-14 23:22:15 UTC

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Package RcppAlgos updated to version 2.2.0 with previous version 2.1.0 dated 2018-09-11

Title: High Performance Tools for Combinatorics and Computational Mathematics
Description: Provides optimized functions implemented in C++ with 'Rcpp' for solving problems in combinatorics and computational mathematics. There are combination/permutation functions that are both flexible as well as efficient with respect to speed and memory. Constraint parameters allow for generation of all combinations/permutations of a vector meeting specific criteria (e.g. finding all combinations such that the sum is less than a bound). Capable of generating specific combinations/permutations (e.g. retrieve only the nth lexicographical result) which sets up nicely for parallelization as well as random sampling. Gmp support permits exploration where the total number of results is large (e.g. comboSample(10000, 500, n = 4)). Additionally, there are several highly efficient number theoretic functions that are useful for problems common in computational mathematics. Some of these functions make use of the fast integer division library 'libdivide' by <http://ridiculousfish.com>. The primeSieve function is based on the segmented sieve of Eratosthenes implementation by Kim Walisch. It is capable of generating all primes less than a billion in just over 1 second. It can also quickly generate prime numbers over a range (e.g. primeSieve(10^13, 10^13+10^9)). Finally, there is a prime counting function that implements a simple variations of Legendre's formula based on the algorithm by Kim Walisch.
Author: Joseph Wood
Maintainer: Joseph Wood <jwood000@gmail.com>

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Package gbm updated to version 2.1.4 with previous version 2.1.3 dated 2017-03-21

Title: Generalized Boosted Regression Models
Description: An implementation of extensions to Freund and Schapire's AdaBoost algorithm and Friedman's gradient boosting machine. Includes regression methods for least squares, absolute loss, t-distribution loss, quantile regression, logistic, multinomial logistic, Poisson, Cox proportional hazards partial likelihood, AdaBoost exponential loss, Huberized hinge loss, and Learning to Rank measures (LambdaMart). Originally developed by Greg Ridgeway.
Author: Brandon Greenwell [aut, cre] (<https://orcid.org/0000-0002-8120-0084>), Bradley Boehmke [aut] (<https://orcid.org/0000-0002-3611-8516>), Jay Cunningham [aut], GBM Developers [aut] (https://github.com/gbm-developers)
Maintainer: ORPHANED

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Package conf updated to version 1.3.3 with previous version 1.3.2 dated 2018-09-10

Title: Visualization and Analysis of Statistical Measures of Confidence
Description: Enables: (1) plotting two-dimensional confidence regions, (2) coverage analysis of confidence region simulations and (3) calculating confidence intervals and the associated actual coverage for binomial proportions. Each is given in greater detail next. (1) Plots the two-dimensional confidence region for probability distribution parameters (supported distribution suffixes: gamma, invgauss, llogis, lnorm, norm, unif, weibull) corresponding to a user given dataset and level of significance. The crplot() algorithm plots more points in areas of greater curvature to ensure a smooth appearance throughout the confidence region boundary. An alternative heuristic plots a specified number of points at roughly uniform intervals along its boundary. Both heuristics build upon the radial profile log-likelihood ratio technique for plotting two-dimensional confidence regions given by Jaeger (2016) <doi:10.1080/00031305.2016.1182946>. (2) Performs confidence region coverage simulations for a random sample drawn from a user-specified parametric population distribution, or for a user-specified dataset and point of interest with coversim(). (3) Calculates confidence interval bounds for a binomial proportion with binomTest(), calculates the actual coverage with binomTestCoverage(), and plots the actual coverage with binomTestCoveragePlot(). Calculates confidence interval bounds for the binomial proportion using an ensemble of constituent confidence intervals with binomTestEnsemble().
Author: Christopher Weld [aut, cre] (<https://orcid.org/0000-0001-5902-9738>), Hayeon Park [aut], Lawrence Leemis [aut], Andrew Loh [ctb], Yuan Chang [ctb], Brock Crook [ctb], Xin Zhang [ctb]
Maintainer: Christopher Weld <ceweld@email.wm.edu>

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Package asht updated to version 0.9.4 with previous version 0.9.3 dated 2017-10-14

Title: Applied Statistical Hypothesis Tests
Description: Gives some hypothesis test functions (sign test, median and other quantile tests, Wilcoxon signed rank test, coefficient of variation test, test of normal variance, test on weighted sums of Poisson [see Fay and Kim <doi:10.1002/bimj.201600111>], sample size for t-tests with different variances and non-equal n per arm, Behrens-Fisher test, nonparametric ABC intervals, Wilcoxon-Mann-Whitney test [with effect estimates and confidence intervals, see Fay and Malinovsky <doi:10.1002/sim.7890>], two-sample melding tests [see Fay, Proschan, and Brittain <doi:10.1111/biom.12231>], one-way ANOVA allowing var.equal=FALSE [see Brown and Forsythe, 1974, Biometrics]). The focus is on methods that have compatible confidence intervals.
Author: Michael P. Fay
Maintainer: Michael P. Fay <mfay@niaid.nih.gov>

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Package CovTools updated to version 0.5.0 with previous version 0.4.0 dated 2018-09-01

Title: Statistical Tools for Covariance Analysis
Description: Covariance is of universal prevalence across various disciplines within statistics. We provide a rich collection of geometric and inferential tools for convenient analysis of covariance structures, topics including distance measures, mean covariance estimator, covariance hypothesis test for one-sample and two-sample cases, and covariance estimation. For an introduction to covariance in multivariate statistical analysis, see Schervish (1987) <doi:10.1214/ss/1177013111>.
Author: Kyoungjae Lee [aut], Lizhen Lin [ctb], Kisung You [aut, cre] (<https://orcid.org/0000-0002-8584-459X>)
Maintainer: Kisung You <kyou@nd.edu>

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Package demogR updated to version 0.6.0 with previous version 0.5.1 dated 2018-08-03

Title: Analysis of Age-Structured Demographic Models
Description: Construction and analysis of matrix population models in R.
Author: James Holland Jones [aut] <jhj1@stanford.edu>, Jim Oeppen [ctb]
Maintainer: Hana Sevcikova <hanas@uw.edu>

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Package poolfstat updated to version 1.0.0 with previous version 0.0.1 dated 2018-03-14

Title: Computing F-Statistics from Pool-Seq Data
Description: Functions for the computation of F-statistics from Pool-Seq data in population genomics studies. The package also includes several utilities to manipulate Pool-Seq data stored in standard format ('vcf' and 'rsync' files as obtained from the popular software 'VarScan' and 'PoPoolation' respectively) and perform conversion to alternative format (as used in the 'BayPass' and 'SelEstim' software).
Author: Mathieu Gautier, Valentin Hivert and Renaud Vitalis
Maintainer: Mathieu Gautier <mathieu.gautier@inra.fr>

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Package mkin updated to version 0.9.47.5 with previous version 0.9.47.2 dated 2018-07-19

Title: Kinetic Evaluation of Chemical Degradation Data
Description: Calculation routines based on the FOCUS Kinetics Report (2006, 2014). Includes a function for conveniently defining differential equation models, model solution based on eigenvalues if possible or using numerical solvers and a choice of the optimisation methods made available by the 'FME' package. If a C compiler (on windows: 'Rtools') is installed, differential equation models are solved using compiled C functions. Please note that no warranty is implied for correctness of results or fitness for a particular purpose.
Author: Johannes Ranke [aut, cre, cph] (<https://orcid.org/0000-0003-4371-6538>), Katrin Lindenberger [ctb], René Lehmann [ctb], Eurofins Regulatory AG [cph]
Maintainer: Johannes Ranke <jranke@uni-bremen.de>

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Package kitagawa updated to version 2.2-2 with previous version 2.1-0 dated 2013-10-04

Title: Spectral Response of Water Wells to Harmonic Strain and Pressure Signals
Description: Provides tools to calculate the theoretical hydrodynamic response of an aquifer undergoing harmonic straining or pressurization, or analyze measured responses. There are two classes of models here: (1) for sealed wells, based on the model of Kitagawa et al (2011, <doi:10.1029/2010JB007794>), and (2) for open wells, based on the models of Cooper et al (1965, <doi:10.1029/JZ070i016p03915>), Hsieh et al (1987, <doi:10.1029/WR023i010p01824>), Rojstaczer (1988, <doi:10.1029/JB093iB11p13619>), and Liu et al (1989, <doi:10.1029/JB094iB07p09453>). These models treat strain (or aquifer head) as an input to the physical system, and fluid-pressure (or water height) as the output. The applicable frequency band of these models is characteristic of seismic waves, atmospheric pressure fluctuations, and solid earth tides.
Author: Andrew J Barbour
Maintainer: Andrew J Barbour <andy.barbour@gmail.com>

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Package crawl updated to version 2.2.1 with previous version 2.2.0 dated 2018-08-25

Title: Fit Continuous-Time Correlated Random Walk Models to Animal Movement Data
Description: Fit continuous-time correlated random walk models with time indexed covariates to animal telemetry data. The model is fit using the Kalman-filter on a state space version of the continuous-time stochastic movement process.
Author: Devin S. Johnson [aut, cre], Josh London [aut], Kenady Wilson [ctb]
Maintainer: Devin S. Johnson <devin.johnson@noaa.gov>

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Package reglogit updated to version 1.2-6 with previous version 1.2-5 dated 2017-11-19

Title: Simulation-Based Regularized Logistic Regression
Description: Regularized (polychotomous) logistic regression by Gibbs sampling. The package implements subtly different MCMC schemes with varying efficiency depending on the data type (binary v. binomial, say) and the desired estimator (regularized maximum likelihood, or Bayesian maximum a posteriori/posterior mean, etc.) through a unified interface.
Author: Robert B. Gramacy <rbg@vt.edu>
Maintainer: Robert B. Gramacy <rbg@vt.edu>

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Package monomvn updated to version 1.9-8 with previous version 1.9-7 dated 2017-01-08

Title: Estimation for Multivariate Normal and Student-t Data with Monotone Missingness
Description: Estimation of multivariate normal and student-t data of arbitrary dimension where the pattern of missing data is monotone. Through the use of parsimonious/shrinkage regressions (plsr, pcr, lasso, ridge, etc.), where standard regressions fail, the package can handle a nearly arbitrary amount of missing data. The current version supports maximum likelihood inference and a full Bayesian approach employing scale-mixtures for Gibbs sampling. Monotone data augmentation extends this Bayesian approach to arbitrary missingness patterns. A fully functional standalone interface to the Bayesian lasso (from Park & Casella), Normal-Gamma (from Griffin & Brown), Horseshoe (from Carvalho, Polson, & Scott), and ridge regression with model selection via Reversible Jump, and student-t errors (from Geweke) is also provided.
Author: Robert B. Gramacy <rbg@vt.edu>
Maintainer: Robert B. Gramacy <rbg@vt.edu>

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Package mize updated to version 0.2.0 with previous version 0.1.1 dated 2017-07-14

Title: Unconstrained Numerical Optimization Algorithms
Description: Optimization algorithms implemented in R, including conjugate gradient (CG), Broyden-Fletcher-Goldfarb-Shanno (BFGS) and the limited memory BFGS (L-BFGS) methods. Most internal parameters can be set through the call interface. The solvers hold up quite well for higher-dimensional problems.
Author: James Melville [aut, cre]
Maintainer: James Melville <jlmelville@gmail.com>

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Package iotables updated to version 0.3.4 with previous version 0.3.3 dated 2018-09-10

Title: Importing and Manipulating Symmetric Input-Output Tables
Description: Pre-processing tasks related to working with Eurostat's symmetric input-output tables and provide basic input-output economics calculations. The package is a part of rOpenGov <http://ropengov.github.io/> to open source open government initiatives.
Author: Daniel Antal [aut, cre]
Maintainer: Daniel Antal <daniel.antal@ceemid.eu>

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Package cruts updated to version 0.5 with previous version 0.4 dated 2018-05-22

Title: Interface to Climatic Research Unit Time-Series Version 3.21 Data
Description: Functions for reading in and manipulating CRU TS3.21: Climatic Research Unit (CRU) Time-Series (TS) Version 3.21 data.
Author: Benjamin M. Taylor Additional contributions Bikash Parida Jacob Davies
Maintainer: Benjamin M. Taylor <b.taylor1@lancaster.ac.uk>

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Package AnaCoDa updated to version 0.1.2 with previous version 0.1.1 dated 2018-02-12

Title: Analysis of Codon Data under Stationarity using a Bayesian Framework
Description: Is a collection of models to analyze genome scale codon data using a Bayesian framework. Provides visualization routines and checkpointing for model fittings. Currently published models to analyze gene data for selection on codon usage based on Ribosome Overhead Cost (ROC) are: ROC (Gilchrist et al. (2015) <doi:10.1093/gbe/evv087>), and ROC with phi (Wallace & Drummond (2013) <doi:10.1093/molbev/mst051>). In addition 'AnaCoDa' contains three currently unpublished models. The FONSE (First order approximation On NonSense Error) model analyzes gene data for selection on codon usage against of nonsense error rates. The PA (PAusing time) and PANSE (PAusing time + NonSense Error) models use ribosome footprinting data to analyze estimate ribosome pausing times with and without nonsense error rate from ribosome footprinting data.
Author: Cedric Landerer [aut, cre], Gabriel Hanas [ctb], Jeremy Rogers [ctb], Alex Cope [ctb], Denizhan Pak [ctb]
Maintainer: Cedric Landerer <cedric.landerer@gmail.com>

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Package alakazam updated to version 0.2.11 with previous version 0.2.10 dated 2018-03-30

Title: Immunoglobulin Clonal Lineage and Diversity Analysis
Description: Provides methods for high-throughput adaptive immune receptor repertoire sequencing (AIRR-Seq; Rep-Seq) analysis. In particular, immunoglobulin (Ig) sequence lineage reconstruction, lineage topology analysis, diversity profiling, amino acid property analysis and gene usage. Citations: Gupta and Vander Heiden, et al (2017) <doi:10.1093/bioinformatics/btv359>, Stern, Yaari and Vander Heiden, et al (2014) <doi:10.1126/scitranslmed.3008879>.
Author: Jason Vander Heiden [aut, cre], Namita Gupta [aut], Susanna Marquez [ctb], Daniel Gadala-Maria [ctb], Ruoyi Jiang [ctb], Nima Nouri [ctb], Steven Kleinstein [aut, cph]
Maintainer: Jason Vander Heiden <jason.vanderheiden@yale.edu>

Diff between alakazam versions 0.2.10 dated 2018-03-30 and 0.2.11 dated 2018-09-14

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Package sgmcmc updated to version 0.2.3 with previous version 0.2.2 dated 2018-04-11

Title: Stochastic Gradient Markov Chain Monte Carlo
Description: Provides functions that performs popular stochastic gradient Markov chain Monte Carlo (SGMCMC) methods on user specified models. The required gradients are automatically calculated using 'TensorFlow' <https://www.tensorflow.org/>, an efficient library for numerical computation. This means only the log likelihood and log prior functions need to be specified. The methods implemented include stochastic gradient Langevin dynamics (SGLD), stochastic gradient Hamiltonian Monte Carlo (SGHMC), stochastic gradient Nose-Hoover thermostat (SGNHT) and their respective control variate versions for increased efficiency. References: M. Welling, Y. W. Teh (2011) <http://www.icml-2011.org/papers/398_icmlpaper.pdf>; T. Chen, E. B. Fox, C. E. Guestrin (2014) <arXiv:1402.4102>; N. Ding, Y. Fang, R. Babbush, C. Chen, R. D. Skeel, H. Neven (2014) <https://papers.nips.cc/paper/5592-bayesian-sampling-using-stochastic-gradient-thermostats>; J. Baker, P. Fearnhead, E. B. Fox, C. Nemeth (2017) <arXiv:1706.05439>.
Author: Jack Baker [aut, cre, cph], Christopher Nemeth [aut, cph], Paul Fearnhead [aut, cph], Emily B. Fox [aut, cph], STOR-i [cph]
Maintainer: Jack Baker <j.baker1@lancaster.ac.uk>

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New package mstrio with initial version 10.11.1
Package: mstrio
Type: Package
Title: Interface for 'MicroStrategy' REST API
Version: 10.11.1
Author: Scott Rigney
Maintainer: Scott Rigney <srigney@microstrategy.com>
Description: Interface for creating data sets and extracting data through the 'MicroStrategy' REST API. Access the demo API at <https://demo.microstrategy.com/MicroStrategyLibrary/api-docs/index.html>.
License: Apache License 2.0 | file LICENSE
Encoding: UTF-8
LazyData: true
Depends: R (>= 3.4.0)
Imports: httr (>= 1.3.1), openssl (>= 1.0.1), jsonlite (>= 1.5), methods
Suggests: knitr, rmarkdown, testthat
VignetteBuilder: knitr
RoxygenNote: 6.0.1
Collate: 'authentication.R' 'cubes.R' 'datasets.R' 'formjson.R' 'microstrategy.R' 'parsejson.R' 'projects.R' 'reports.R'
NeedsCompilation: no
Packaged: 2018-09-14 12:16:36 UTC; srigney
Repository: CRAN
Date/Publication: 2018-09-14 15:50:02 UTC

More information about mstrio at CRAN
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Package moveVis updated to version 0.9.8 with previous version 0.9.7 dated 2018-09-10

Title: Movement Data Visualization
Description: Tools to visualize movement data (e.g. from GPS tracking) and temporal changes of environmental data (e.g. from remote sensing) by creating video animations.
Author: Jakob Schwalb-Willmann [aut, cre]
Maintainer: Jakob Schwalb-Willmann <movevis@schwalb-willmann.de>

Diff between moveVis versions 0.9.7 dated 2018-09-10 and 0.9.8 dated 2018-09-14

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Package longmemo updated to version 1.1-1 with previous version 1.0-0 dated 2011-06-15

Title: Statistics for Long-Memory Processes (Book Jan Beran), and Related Functionality
Description: Datasets and Functionality from 'Jan Beran' (1994). Statistics for Long-Memory Processes; Chapman & Hall. Estimation of Hurst (and more) parameters for fractional Gaussian noise, 'fARIMA' and 'FEXP' models.
Author: S scripts originally by Jan Beran <jan.beran@uni-konstanz.de>; Datasets via Brandon Whitcher <brandon@stat.washington.edu>. Toplevel R functions and much more by Martin Maechler.
Maintainer: Martin Maechler <maechler@stat.math.ethz.ch>

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Package fingertipscharts updated to version 0.0.2 with previous version 0.0.1 dated 2018-07-28

Title: Produce Charts that you See on the Fingertips Website
Description: Use Fingertips charts to recreate the visualisations that are displayed on the Fingertips website (<http://fingertips.phe.org.uk/>).
Author: Sebastian Fox [aut, cre]
Maintainer: Sebastian Fox <sebastian.fox@phe.gov.uk>

Diff between fingertipscharts versions 0.0.1 dated 2018-07-28 and 0.0.2 dated 2018-09-14

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Package snow updated to version 0.4-3 with previous version 0.4-2 dated 2016-10-13

Title: Simple Network of Workstations
Description: Support for simple parallel computing in R.
Author: Luke Tierney, A. J. Rossini, Na Li, H. Sevcikova
Maintainer: Luke Tierney <luke-tierney@uiowa.edu>

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Package MmgraphR updated to version 0.3-1 with previous version 0.3 dated 2018-07-25

Title: Graphing for Markov, Hidden Markov, and Mixture Transition Distribution Models
Description: Produces parallel coordinate plots of probability transition matrices from Markov, hidden Markov, and mixture transition distribution models.
Author: Pauline Adamopoulou [aut, cre, cph], Gilbert Ritschard [ths], Andre Berchtold [ths], Reto Buergin [ctb], Ogier Maitre [ctb]
Maintainer: Pauline Adamopoulou <padamopo@gmail.com>

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Package glpkAPI updated to version 1.3.1 with previous version 1.3.0 dated 2015-01-06

Title: R Interface to C API of GLPK
Description: R Interface to C API of GLPK, depends on GLPK Version >= 4.42.
Author: Mayo Roettger [cre], Gabriel Gelius-Dietrich [aut], Louis Luangkesorn [ctb]
Maintainer: Mayo Roettger <mayo.roettger@hhu.de>

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Package txtq updated to version 0.1.0 with previous version 0.0.4 dated 2018-06-15

Title: A Small Message Queue for Parallel Processes
Description: This queue is a data structure that lets parallel processes send and receive messages, and it can help coordinate the work of complicated parallel tasks. Processes can push new messages to the queue, pop old messages, and obtain a log of all the messages ever pushed. File locking preserves the integrity of the data even when multiple processes access the queue simultaneously.
Author: William Michael Landau [aut, cre], Eli Lilly and Company [cph]
Maintainer: William Michael Landau <will.landau@gmail.com>

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Package rsparkling updated to version 0.2.8 with previous version 0.2.5 dated 2018-08-03

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

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Package pimeta updated to version 1.1.0 with previous version 1.0.1 dated 2018-05-10

Title: Prediction Intervals for Random-Effects Meta-Analysis
Description: An implementation of prediction intervals for random-effects meta-analysis: Higgins et al. (2009) <doi:10.1111/j.1467-985X.2008.00552.x>, Partlett and Riley (2017) <doi:10.1002/sim.7140>, and Nagashima et al. (2018) <doi:10.1177/0962280218773520>, <arXiv:1804.01054>.
Author: Kengo Nagashima [aut, cre] (<https://orcid.org/0000-0003-4529-9045>), Hisashi Noma [aut], Toshi A. Furukawa [aut]
Maintainer: Kengo Nagashima <nshi1201@gmail.com>

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New package RtutoR with initial version 1.2
Package: RtutoR
Type: Package
Title: Shiny Apps for Plotting and Exploratory Analysis
Version: 1.2
Date: 2018-09-04
Author: Anup Nair [aut, cre]
Maintainer: Anup Nair <nairanup50695@gmail.com>
Description: Contains Shiny apps for Plotting and Exploratory Analysis. The plotting app provides an automated interface for generating plots using the 'ggplot2' package. Current version of this app supports 10 different plot types along with options to manipulate specific aesthetics and controls related to each plot type. Exploratory Analysis app helps generates an Exploratory analysis report (in PowerPoint format) comprising of Univariate and Bivariate plots & related summary tables.
Depends: R (>= 3.1.0)
License: GPL
Imports: dplyr (>= 0.7.4), ggplot2 (>= 2.2.1), shiny, shinydashboard, rmarkdown, DT, shinyBS, shinyjs, ggthemes, plotly, rlang, FSelector, officer, colourpicker, tidyr, devtools
LazyData: TRUE
RoxygenNote: 6.1.0
NeedsCompilation: no
Packaged: 2018-09-04 07:03:53 UTC; anup.a.nair
Repository: CRAN
Date/Publication: 2018-09-14 07:50:07 UTC
Encoding: UTF-8

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Permanent link

Package RNOmni updated to version 0.5.0 with previous version 0.4.0 dated 2018-05-16

Title: Omnibus Test for Genetic Association Analysis using the Rank Normal Transformation
Description: Implementation of genetic association tests for continuous outcomes utilizing the rank-based inverse normal transformation (INT). For outcomes whose residual distribution is heavily skewed or enriched for outliers, INT-based tests provided valid inference and improved power. The primary contribution is a rank normal omnibus test (RNOmni), which synthesizes two complementary INT-based approaches. In simulations against non-normal phenotypes, the omnibus test controlled the type I error in the absence of genetic associations, and improved power in the presence of genetic associations. Under the same settings, standard linear regression variously failed to control the type I error in the absence of associations, and was underpowered in the presence of associations.
Author: Zachary McCaw [aut, cre]
Maintainer: Zachary McCaw <zmccaw@g.harvard.edu>

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Package LabourMarketAreas updated to version 3.2.2 with previous version 3.2 dated 2017-12-07

Title: Identification, Tuning, Visualisation and Analysis of Labour Market Areas
Description: Produces Labour Market Areas from commuting flows available at elementary territorial units. It provides tools for automatic tuning based on spatial contiguity. It also allows for statistical analyses and visualisation of the new functional geography.
Author: Daniela Ichim, Luisa Franconi, Michele D'Alo', Guido van den Heuvel
Maintainer: Luisa Franconi <franconi@istat.it>

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Package itunesr updated to version 0.1.2 with previous version 0.1.1 dated 2018-03-05

Title: Access iTunes App Store Ratings and Reviews using R
Description: To enable 'iOS' App Developers to access iTunes App Store Ratings and Reviews using R to extract Basic App Information and Reviews submitted by their App users, Since Apple Store does not provide this straightforward.
Author: AbdulMajedRaja RS [aut, cre]
Maintainer: AbdulMajedRaja RS <amrrs.data@gmail.com>

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Package fts updated to version 0.9.9.2 with previous version 0.9.9.1 dated 2018-07-29

Title: R Interface to 'tslib' (a Time Series Library in C++)
Description: Fast operations for time series objects.
Author: Whit Armstrong <armstrong.whit@gmail.com>
Maintainer: Whit Armstrong <armstrong.whit@gmail.com>

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Package dLagM updated to version 1.0.6 with previous version 1.0.2 dated 2018-01-17

Title: Time Series Regression Models with Distributed Lag Models
Description: Provides time series regression models with one predictor using finite distributed lag models, polynomial (Almon) distributed lag models, geometric distributed lag models with Koyck transformation, and autoregressive distributed lag models. It also consists of functions for computation of h-step ahead forecasts from these models. See Baltagi (2011) <doi:10.1007/978-3-642-20059-5> for more information.
Author: Haydar Demirhan [aut, cre, cph] (<https://orcid.org/0000-0002-8565-4710>)
Maintainer: Haydar Demirhan <haydar.demirhan@rmit.edu.au>

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Package BMA updated to version 3.18.9 with previous version 3.18.8 dated 2018-03-22

Title: Bayesian Model Averaging
Description: Package for Bayesian model averaging and variable selection for linear models, generalized linear models and survival models (cox regression).
Author: Adrian Raftery <raftery@uw.edu>, Jennifer Hoeting, Chris Volinsky, Ian Painter, Ka Yee Yeung
Maintainer: Hana Sevcikova <hanas@uw.edu>

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Package cleandata updated to version 0.2.0 with previous version 0.1.0 dated 2018-07-21

Title: To Inspect, Impute, Encode, and Partition Data; and to Keep Track of This Process
Description: Functions to work with data frames to prepare data for further analysis. The functions for imputation, encoding, and Partitioning can produce log files to keep track of data manipulation process.
Author: Sherry Zhao
Maintainer: Sherry Zhao <sxzhao@gwu.edu>

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 man/partition_random.Rd |only
 vignettes               |only
 20 files changed, 111 insertions(+), 71 deletions(-)

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Package MCMCpack updated to version 1.4-4 with previous version 1.4-3 dated 2018-05-15

Title: Markov Chain Monte Carlo (MCMC) Package
Description: Contains functions to perform Bayesian inference using posterior simulation for a number of statistical models. Most simulation is done in compiled C++ written in the Scythe Statistical Library Version 1.0.3. All models return 'coda' mcmc objects that can then be summarized using the 'coda' package. Some useful utility functions such as density functions, pseudo-random number generators for statistical distributions, a general purpose Metropolis sampling algorithm, and tools for visualization are provided.
Author: Andrew D. Martin [aut], Kevin M. Quinn [aut], Jong Hee Park [aut,cre], Ghislain Vieilledent [ctb], Michael Malecki[ctb], Matthew Blackwell [ctb], Keith Poole [ctb], Craig Reed [ctb], Ben Goodrich [ctb], Ross Ihaka [cph], The R Development Core Team [cph], The R Foundation [cph], Pierre L'Ecuyer [cph], Makoto Matsumoto [cph], Takuji Nishimura [cph]
Maintainer: Jong Hee Park <jongheepark@snu.ac.kr>

Diff between MCMCpack versions 1.4-3 dated 2018-05-15 and 1.4-4 dated 2018-09-14

 DESCRIPTION           |    8 ++++----
 MD5                   |    6 +++---
 src/cHDPHMMpoisson.cc |    2 +-
 src/rng.h             |    4 +++-
 4 files changed, 11 insertions(+), 9 deletions(-)

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Package mcca updated to version 0.4.0 with previous version 0.3.0 dated 2018-04-09

Title: Multi-Category Classification Accuracy
Description: It contains six common multi-category classification accuracy evaluation measures: Hypervolume Under Manifold (HUM), described in Li and Fine (2008) <doi:10.1093/biostatistics/kxm050>. Correct Classification Percentage (CCP), Integrated Discrimination Improvement (IDI), Net Reclassification Improvement (NRI), R-Squared Value (RSQ), described in Li, Jiang and Fine (2013) <doi:10.1093/biostatistics/kxs047>. Polytomous Discrimination Index (PDI), described in Van Calster et al. (2012) <doi:10.1007/s10654-012-9733-3>. Li et al. (2018) <doi:10.1177/0962280217692830>.
Author: Ming Gao, Jialiang Li
Maintainer: Ming Gao <gaoming96@sjtu.edu.cn>

Diff between mcca versions 0.3.0 dated 2018-04-09 and 0.4.0 dated 2018-09-14

 DESCRIPTION |    6 -
 MD5         |    6 -
 R/ccp.R     |  138 ++++++++++++++++++++--------------------
 R/nri.R     |  202 ++----------------------------------------------------------
 4 files changed, 83 insertions(+), 269 deletions(-)

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