Sat, 14 May 2016

Package TSdist updated to version 3.3 with previous version 3.2 dated 2016-02-12

Title: Distance Measures for Time Series Data
Description: A set of commonly used distance measures and some additional functions which, although initially not designed for this purpose, can be used to measure the dissimilarity between time series. These measures can be used to perform clustering, classification or other data mining tasks which require the definition of a distance measure between time series.
Author: Usue Mori, Alexander Mendiburu, J.A. Lozano
Maintainer: Usue Mori <usue.mori@ehu.eus>

Diff between TSdist versions 3.2 dated 2016-02-12 and 3.3 dated 2016-05-14

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Package trend updated to version 0.2.0 with previous version 0.1.0 dated 2016-01-06

Title: Non-Parametric Trend Tests and Change-Point Detection
Description: The analysis of environmental data often requires the detection of trends and change-points. This package provides the Mann-Kendall Trend Test, seasonal Mann-Kendall Test, correlated seasonal Mann-Kendall Test, partial Mann-Kendall Trend test, (Seasonal) Sen's slope, partial correlation trend test and change-point test after Pettitt.
Author: Thorsten Pohlert
Maintainer: Thorsten Pohlert <thorsten.pohlert@gmx.de>

Diff between trend versions 0.1.0 dated 2016-01-06 and 0.2.0 dated 2016-05-14

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More information about trend at CRAN
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New package rr with initial version 1.3.1
Package: rr
Version: 1.3.1
Date: 2016-5-13
Title: Statistical Methods for the Randomized Response Technique
Author: Graeme Blair <graeme.blair@columbia.edu>, Yang-Yang Zhou <yz3@princeton.edu>, Kosuke Imai <kimai@princeton.edu>
Maintainer: Graeme Blair <graeme.blair@columbia.edu>
Depends: R (>= 3.0.0), utils
Imports: MASS, arm, coda
Description: Enables researchers to conduct multivariate statistical analyses of survey data with randomized response technique items from several designs, including mirrored question, forced question, and unrelated question. This includes regression with the randomized response as the outcome and logistic regression with the randomized response item as a predictor. In addition, tools for conducting power analysis for designing randomized response items are included. The package implements methods described in Blair, Imai, and Zhou (2015) ''Design and Analysis of the Randomized Response Technique,'' Working paper available at <http://graemeblair.com/papers/randresp.pdf>.
LazyLoad: yes
LazyData: yes
License: GPL (>= 3)
Suggests: testthat
RoxygenNote: 5.0.1
NeedsCompilation: yes
Packaged: 2016-05-14 18:52:38 UTC; gblair
X-CRAN-Comment: Archived on 2016-05-02 as check problems were not corrected despite reminders.
Repository: CRAN
Date/Publication: 2016-05-14 23:31:33

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Package Rcpp updated to version 0.12.5 with previous version 0.12.4 dated 2016-03-26

Title: Seamless R and C++ Integration
Description: The 'Rcpp' package provides R functions as well as C++ classes which offer a seamless integration of R and C++. Many R data types and objects can be mapped back and forth to C++ equivalents which facilitates both writing of new code as well as easier integration of third-party libraries. Documentation about 'Rcpp' is provided by several vignettes included in this package, via the 'Rcpp Gallery' site at <http://gallery.rcpp.org>, the paper by Eddelbuettel and Francois (2011, JSS), and the book by Eddelbuettel (2013, Springer); see 'citation("Rcpp")' for details on these last two.
Author: Dirk Eddelbuettel, Romain Francois, JJ Allaire, Kevin Ushey, Qiang Kou, Douglas Bates and John Chambers
Maintainer: Dirk Eddelbuettel <edd@debian.org>

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Package pec updated to version 2.4.9 with previous version 2.4.7 dated 2015-10-05

Title: Prediction Error Curves for Risk Prediction Models in Survival Analysis
Description: Validation of risk predictions obtained from survival models and competing risk models based on censored data using inverse weighting and cross-validation.
Author: Thomas A. Gerds
Maintainer: Thomas A. Gerds <tag@biostat.ku.dk>

Diff between pec versions 2.4.7 dated 2015-10-05 and 2.4.9 dated 2016-05-14

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Package lrmest updated to version 3.0 with previous version 1.0 dated 2013-08-31

Title: Different Types of Estimators to Deal with Multicollinearity
Description: When multicollinearity exists among predictor variables of the linear model, least square estimators does not provide a better solution for estimating parameters. To deal with multicollinearity several estimators are proposed in the literature. Some of these estimators are Ordinary Least Square Estimator (OLSE), Ordinary Generalized Ordinary Least Square Estimator (OGOLSE), Ordinary Ridge Regression Estimator (ORRE), Ordinary Generalized Ridge Regression Estimator (OGRRE), Restricted Least Square Estimator (RLSE), Ordinary Generalized Restricted Least Square Estimator (OGRLSE), Ordinary Mixed Regression Estimator (OMRE), Ordinary Generalized Mixed Regression Estimator (OGMRE), Liu Estimator (LE), Ordinary Generalized Liu Estimator (OGLE), Restricted Liu Estimator (RLE), Ordinary Generalized Restricted Liu Estimator (OGRLE), Stochastic Restricted Liu Estimator (SRLE), Ordinary Generalized Stochastic Restricted Liu Estimator (OGSRLE), Type (1),(2),(3) Liu Estimator (Type-1,2,3 LTE), Ordinary Generalized Type (1),(2),(3) Liu Estimator (Type-1,2,3 OGLTE), Type (1),(2),(3) Adjusted Liu Estimator (Type-1,2,3 ALTE), Ordinary Generalized Type (1),(2),(3) Adjusted Liu Estimator (Type-1,2,3 OGALTE), Almost Unbiased Ridge Estimator (AURE), Ordinary Generalized Almost Unbiased Ridge Estimator (OGAURE), Almost Unbiased Liu Estimator (AULE), Ordinary Generalized Almost Unbiased Liu Estimator (OGAULE), Stochastic Restricted Ridge Estimator (SRRE), Ordinary Generalized Stochastic Restricted Ridge Estimator (OGSRRE), Restricted Ridge Regression Estimator (RRRE) and Ordinary Generalized Restricted Ridge Regression Estimator (OGRRRE). To select the best estimator in a practical situation the Mean Square Error (MSE) is used. Using this package scalar MSE value of all the above estimators and Prediction Sum of Square (PRESS) values of some of the estimators can be obtained, and the variation of the MSE and PRESS values for the relevant estimators can be shown graphically.
Author: Ajith Dissanayake [aut, cre], P. Wijekoon [aut], R-core [cph]
Maintainer: Ajith Dissanayake <sudeera333@gmail.com>

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Package kdecopula updated to version 0.6.0 with previous version 0.5.0 dated 2016-02-16

Title: Kernel Smoothing for Bivariate Copula Densities
Description: Provides fast implementations of kernel smoothing techniques for bivariate copula densities, in particular density estimation and resampling.
Author: Thomas Nagler [aut, cre]
Maintainer: Thomas Nagler <thomas.nagler@tum.de>

Diff between kdecopula versions 0.5.0 dated 2016-02-16 and 0.6.0 dated 2016-05-14

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Package installr updated to version 0.17.8 with previous version 0.17.5 dated 2016-03-20

Title: Using R to Install Stuff (Such As: R, Rtools, RStudio, Git, and More!)
Description: R is great for installing software. Through the 'installr' package you can automate the updating of R (on Windows, using updateR()) and install new software. Software installation is initiated through a GUI (just run installr()), or through functions such as: install.Rtools(), install.pandoc(), install.git(), and many more. The updateR() command performs the following: finding the latest R version, downloading it, running the installer, deleting the installation file, copy and updating old packages to the new R installation.
Author: Tal Galili [aut, cre, cph] (http://www.r-statistics.com), Barry Rowlingson [ctb], Boris Hejblum [ctb], Dason [ctb], Felix Schonbrodt [ctb], G. Grothendieck [ctb], GERGELY DAROCZI [ctb], Heuristic Andrew [ctb], James [ctb] (http://stackoverflow.com/users/269476/james), Thomas Leeper [ctb] (http://thomasleeper.com/), VitoshKa [ctb], Yihui Xie [ctb] (http://yihui.name), Michael Friendly [ctb] (http://datavis.ca/), Kornelius Rohmeyer [ctb] (http://algorithm-forge.com/techblog/), Dieter Menne [ctb], Tyler Hunt [ctb] (https://github.com/JackStat), Takekatsu Hiramura [ctb] (https://github.com/hiratake55), Berry Boessenkool [ctb] (https://github.com/BerryBoessenkool)
Maintainer: Tal Galili <tal.galili@gmail.com>

Diff between installr versions 0.17.5 dated 2016-03-20 and 0.17.8 dated 2016-05-14

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Package geneNetBP updated to version 2.0.0 with previous version 1.0.0 dated 2016-03-17

Title: Belief Propagation in Genotype-Phenotype Networks
Description: Belief propagation methods in genotype-phenotype networks (Conditional Gaussian and Discrete Bayesian Networks) to propagate phenotypic evidence through the network.
Author: Janhavi Moharil
Maintainer: Janhavi Moharil <janhavim@buffalo.edu>

Diff between geneNetBP versions 1.0.0 dated 2016-03-17 and 2.0.0 dated 2016-05-14

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Package enveomics.R updated to version 1.1.0 with previous version 1.0.1 dated 2016-03-06

Title: Various R Functions from the Kostas Lab
Description: A collection of R functions of common use in the Kostas Lab for microbial ecology.
Author: Luis M. Rodriguez-R [aut, cre]
Maintainer: Luis M. Rodriguez-R <lmrodriguezr@gmail.com>

Diff between enveomics.R versions 1.0.1 dated 2016-03-06 and 1.1.0 dated 2016-05-14

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New package dnc with initial version 1.1
Package: dnc
Type: Package
Title: Dynamic Network Clustering
Version: 1.1
Date: 2016-05-06
Author: Daniel K. Sewell
Maintainer: Dan Sewell <daniel-sewell@uiowa.edu>
Description: Community detection for dynamic networks, i.e., networks measured repeatedly over a sequence of discrete time points, using a latent space approach.
License: GPL (>= 2)
Imports: Rcpp (>= 0.12.4), igraph, MCMCpack, vegan, skmeans, plot3D, plot3Drgl, BayesLogit, movMF, tcltk, stats, grDevices, graphics
LinkingTo: Rcpp, RcppArmadillo
Depends: R (>= 3.2.3)
LazyData: true
NeedsCompilation: yes
Packaged: 2016-05-14 19:51:39 UTC; daniel-admin
Repository: CRAN
Date/Publication: 2016-05-14 23:36:56

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New package SSL with initial version 0.1
Package: SSL
Type: Package
Title: Semi-Supervised Learning
Version: 0.1
Date: 2016-05-01
Author: Junxiang Wang
Maintainer: Junxiang Wang <xianggebenben@163.com>
Description: Semi-supervised learning has attracted the attention of machine learning community because of its high accuracy with less annotating effort compared with supervised learning.The question that semi-supervised learning wants to address is: given a relatively small labeled dataset and a large unlabeled dataset, how to design classification algorithms learning from both ? This package is a collection of some classical semi-supervised learning algorithms in the last few decades.
License: GPL (>= 3)
LazyData: TRUE
RoxygenNote: 5.0.1
Depends: R (>= 3.2)
Imports: NetPreProc (>= 1.1), Rcpp (>= 0.12.2), caret (>= 6.0-52), proxy (>= 0.4-15), xgboost (>= 0.4), klaR (>= 0.6-12), e1071 (>= 1.6-7), stats (>= 3.2)
LinkingTo: Rcpp
NeedsCompilation: yes
Packaged: 2016-05-14 13:26:18 UTC; Wangjunxiang
Repository: CRAN
Date/Publication: 2016-05-14 23:12:09

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New package mcPAFit with initial version 0.1.1
Package: mcPAFit
Type: Package
Title: Estimating Node Fitness from a Single Network Snapshot by Markov Chain Monte Carlo
Version: 0.1.1
Date: 2016-05-14
Author: Thong Pham, Paul Sheridan, Hidetoshi Shimodaira
Maintainer: Thong Pham <thongpham@thongpham.net>
Description: A Markov chain Monte Carlo method is provided to estimate fitness from a single network snapshot. Conventional methods require the complete information about the appearance order of nodes and edges in the network. This package performs inference on the timeline space, and so does not require such information.
License: GPL-3
Depends: R(>= 2.10.0)
Imports: Rcpp (>= 0.11.3) , grDevices, graphics, stats, RColorBrewer, PAFit
LinkingTo: Rcpp
LazyData: True
NeedsCompilation: yes
Suggests: R.rsp
Packaged: 2016-05-14 07:25:06 UTC; pham
Repository: CRAN
Date/Publication: 2016-05-14 22:42:22

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Package cricketr updated to version 0.0.13 with previous version 0.0.12 dated 2016-01-01

Title: Analyze Cricketers 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.
Author: Tinniam V Ganesh
Maintainer: Tinniam V Ganesh <tvganesh.85@gmail.com>

Diff between cricketr versions 0.0.12 dated 2016-01-01 and 0.0.13 dated 2016-05-14

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New package rollbar with initial version 0.1.0
Package: rollbar
Type: Package
Title: Error Tracking and Logging
Version: 0.1.0
Date: 2016-05-12
Authors@R: person("Andrew", "Kane", email = "andrew@chartkick.com", role = c("aut", "cre"))
Description: Reports errors and messages to Rollbar, the error tracking platform <https://rollbar.com>.
License: MIT + file LICENSE
LazyData: TRUE
Imports: httr
RoxygenNote: 5.0.1
NeedsCompilation: no
Packaged: 2016-05-14 02:40:29 UTC; andrew
Author: Andrew Kane [aut, cre]
Maintainer: Andrew Kane <andrew@chartkick.com>
Repository: CRAN
Date/Publication: 2016-05-14 09:18:57

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Package reproducer updated to version 0.1.5 with previous version 0.1.4 dated 2016-01-25

Title: Reproduce Statistical Analyses and Meta-Analyses
Description: The reproducer R package includes data analysis functions and data sets (e.g., related to software defect prediction) to streamline reproducible research in software engineering.
Author: Lech Madeyski [cre, aut, ctb], Marian Jureczko [ctb] (Data contributor), Barbara Kitchenham [ctb] (Data contributor), David Budgen [ctb] (Data contributor), Pearl Brereton [ctb] (Data contributor), Jacky Keung [ctb] (Data contributor), Stuart Charters [ctb] (Data contributor), Shirley Gibbs [ctb] (Data contributor), Amnart Pohthong [ctb] (Data contributor)
Maintainer: Lech Madeyski <lech.madeyski@gmail.com>

Diff between reproducer versions 0.1.4 dated 2016-01-25 and 0.1.5 dated 2016-05-14

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Package protViz updated to version 0.2.15 with previous version 0.2.9 dated 2014-09-30

Title: Visualizing and Analyzing Mass Spectrometry Related Data in Proteomics
Description: This R package helps with quality checks, visualizations and analysis of mass spectrometry data, coming from proteomics experiments. The package is developed, tested and used at the Functional Genomics Center Zurich. We use this package mainly for prototyping, teaching, and having fun with proteomics data. But it can also be used to do data analysis for small scale data sets.
Author: Christian Panse <cp@fgcz.ethz.ch>, Jonas Grossmann <jg@fgcz.ethz.ch>, Simon Barkow-Oesterreicher <sb@fgcz.ethz.ch>
Maintainer: Christian Panse <cp@fgcz.ethz.ch>

Diff between protViz versions 0.2.9 dated 2014-09-30 and 0.2.15 dated 2016-05-14

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Package BIGDAWG updated to version 1.4.0 with previous version 1.3.4 dated 2016-04-09

Title: Case-Control Analysis of Multi-Allelic Loci
Description: Data sets and functions for chi-squared Hardy-Weinberg and case-control association tests of highly polymorphic genetic data [e.g., human leukocyte antigen (HLA) data]. Performs association tests at multiple levels of polymorphism (haplotype, locus and HLA amino-acids) as described in Pappas DJ, Marin W, Hollenbach JA, Mack SJ (2016) <doi:10.1016/j.humimm.2015.12.006>. Combines rare variants to a common class to account for sparse cells in tables as described by Hollenbach JA, Mack SJ, Thomson G, Gourraud PA (2012) <doi:10.1007/978-1-61779-842-9_14>.
Author: Derek Pappas <dpappas@chori.org>, Steve Mack <sjmack@chori.org>, Jill Hollenbach <Jill.Hollenbach@ucsf.edu>
Maintainer: Steve Mack <sjmack@chori.org>

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Package prodigenr updated to version 0.2.7 with previous version 0.2.6 dated 2016-04-29

Title: Research Project Directory Generator
Description: Create a project directory structure, along with typical files for that project. This allows projects to be quickly and easily created, as well as for them to be standardized. Designed specifically with scientists in mind (mainly bio-medical researchers, but likely applies to other fields).
Author: Luke Johnston [aut, cre]
Maintainer: Luke Johnston <lwjohnst@gmail.com>

Diff between prodigenr versions 0.2.6 dated 2016-04-29 and 0.2.7 dated 2016-05-14

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Package dae updated to version 2.7-15 with previous version 2.7-6 dated 2015-11-03

Title: Functions Useful in the Design and ANOVA of Experiments
Description: The content falls into the following groupings: (i) Data, (ii) Factor manipulation functions, (iii) Design functions, (iv) ANOVA functions, (v) Matrix functions, (vi) Projector and canonical efficiency functions, and (vii) Miscellaneous functions. A document 'daeDesignRandomization.pdf', available in the doc subdirectory of the installation directory for 'dae', describes the use of the package for generating randomized layouts for experiments. The ANOVA functions facilitate the extraction of information when the 'Error' function has been used in the call to 'aov'.
Author: Chris Brien <Chris.Brien@unisa.edu.au>.
Maintainer: Chris Brien <Chris.Brien@unisa.edu.au>

Diff between dae versions 2.7-6 dated 2015-11-03 and 2.7-15 dated 2016-05-14

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