Thu, 30 Aug 2012

New package fmt with initial version 1.0
Package: fmt
Type: Package
Title: Variance estimation of FMT method (Fully Moderated t-statistic)
Version: 1.0
Date: 2012-08-30
Author: Lianbo Yu, The Ohio State University
Maintainer: Lianbo Yu
Description: This package computes posterior residual variances to be used in the denominator of a moderated t-statistic from a linear model analysis of microarray data. It is an extension of the moderated t-statistic original proposed by Smyth (2004). LOESS local regression and empirical Bayesian method are used to estimate gene specific prior degrees of freedom and prior variance based on average gene intensity level. The posterior residual variance in the denominator is a weighted average of prior and residual variance and the weights are prior degrees of freedom and residual variance degrees of freedom. The degrees of freedom of the moderated t-statistic is simply the sum of prior and residual variance degrees of freedom.
Suggests: limma
License: GPL-2
Packaged: 2012-08-30 18:57:52 UTC; yu18
Repository: CRAN
Date/Publication: 2012-08-30 19:46:07

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New package Sejong with initial version 0.01
Package: Sejong
Maintainer: Heewon Jeon
License: GPL-3
Title: KoNLP static dictionaries and Sejong project resources.
Author: Heewon Jeon
Version: 0.01
Description: Sejong(http://www.sejong.or.kr/) corpus and Hannanum(http://semanticweb.kaist.ac.kr/home/index.php/HanNanum) dictionaries for KoNLP
URL: https://github.com/haven-jeon/Sejong
Repository: CRAN
Date/Publication: 2012-08-30 18:20:47
Packaged: 2012-08-30 15:50:23 UTC; gogamza
Date: 2012-08-13
Encoding : UTF-8
Depends: R (>= 2.14.0)
Collate: 'onLoad.R'

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New package popReconstruct with initial version 1.0-2
Package: popReconstruct
Type: Package
Title: Reconstruct population counts, fertility, mortality and migration rates of human populations of the recent past.
Version: 1.0-2
Date: 2012-08-30
Author: Mark C. Wheldon
Maintainer: Hana Sevcikova
Description: Implements the Bayesian hierarchical model described by Wheldon, Raftery Clark and Gerland (see: http://www.csss.washington.edu/Papers/wp108.pdf) for simultaneously estimating age-specific population counts, fertility rates, mortality rates and net international migration flows, at the national level.
License: GPL-3
LazyLoad: yes
Depends: coda
Suggests: ggplot2, reshape, gdata
Packaged: 2012-08-30 18:36:13 UTC; hana
Repository: CRAN
Date/Publication: 2012-08-30 18:46:28

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New package commandr with initial version 0.9.3
Package: commandr
Title: Command pattern in R
Version: 0.9.3
Author: Michael Lawrence
Depends: methods
Imports: methods, utils
Description: An S4 representation of the Command design pattern. The Operation class is a simple implementation using closures and supports forward and reverse (undo) evaluation. The more complicated Protocol framework represents each type of command (or analytical protocol) by a formal S4 class. Commands may be grouped and consecutively executed using the Pipeline class. Example use cases include logging, do/undo, analysis pipelines, GUI actions, parallel processing, etc.
Maintainer: Tengfei Yin
License: Artistic-2.0
Packaged: 2012-08-30 16:03:18 UTC; tengfei
Repository: CRAN
Date/Publication: 2012-08-30 18:27:12

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New package C50 with initial version 0.0.9
Package: C50
Type: Package
Title: C5.0 Decision Trees and Rule-Based Models
Version: 0.0.9
Date: 2012-08-30
Author: Max Kuhn, Steve Weston, Nathan Coulter. C code for C5.0 by R. Quinlan
Maintainer: Max Kuhn
Description: C5.0 decision trees and rule-based models for pattern recognition
Depends: R (>= 2.10.0)
License: GPL-3
LazyLoad: yes
Packaged: 2012-08-30 18:17:18 UTC; kuhna03
Repository: CRAN
Date/Publication: 2012-08-30 18:36:30

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Package AICcmodavg updated to version 1.26 with previous version 1.25 dated 2012-08-16

Title: Model selection and multimodel inference based on (Q)AIC(c)
Description: This package includes functions to create model selection tables based on Akaike's information criterion (AIC) and the second-order AIC (AICc), as well as their quasi-likelihood counterparts (QAIC, QAICc). Tables are printed with delta AIC and Akaike weights. The package also features functions to conduct classic model averaging (multimodel inference) for a given parameter of interest and predicted values, as well as a shrinkage version of model averaging parameter estimates. Other handy functions enable the computation of relative variable importance, evidence ratios, and confidence sets for the best model. The present version works with Cox regression ('coxph' class), linear models ('lm' class), generalized linear models ('glm' class), linear models fit by generalized least squares ('gls' class), linear mixed models ('lme' class), generalized linear mixed models ('mer' class), multinomial and ordinal logistic regressions ('multinom', 'polr', 'clm', and 'clmm' classes), robust regression models ('rlm' class), and nonlinear models ('nls' class). The package also supports various models incorporating detection probabilities such as single-season occupancy models ('unmarkedFitOccu' class), multiple-season occupancy models ('unmarkedFitColExt' class), single-season heterogeneity models ('unmarkedFitOccuRN' class), single-season and multiple-season N-mixture models for repeated counts ('unmarkedFitPCount' and 'unmarkedFitPCO' classes, respectively), and distance sampling models ('unmarkedFitDS' and 'unmarkedFitGDS' classes).
Author: Marc J. Mazerolle . Special thanks to T. Ergon for the original idea of storing candidate models in a list.
Maintainer: Marc J. Mazerolle

Diff between AICcmodavg versions 1.25 dated 2012-08-16 and 1.26 dated 2012-08-30

 DESCRIPTION               |   16 +-
 MD5                       |   57 +++++----
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Package MASS updated to version 7.3-21 with previous version 7.3-20 dated 2012-08-01

Title: Support Functions and Datasets for Venables and Ripley's MASS
Description: Functions and datasets to support Venables and Ripley, 'Modern Applied Statistics with S' (4th edition, 2002).
Author: Brian Ripley [aut, cre, cph], Bill Venables [ctb], Kurt Hornik [trl] (partial port ca 1998), Albrecht Gebhardt [trl] (partial port ca 1998), David Firth [ctb]
Maintainer: Brian Ripley

Diff between MASS versions 7.3-20 dated 2012-08-01 and 7.3-21 dated 2012-08-30

 DESCRIPTION    |   10 ++++-----
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Package fpc updated to version 2.1-4 with previous version 2.0-3 dated 2010-11-19

Title: Flexible procedures for clustering
Description: Various methods for clustering and cluster validation. Fixed point clustering. Linear regression clustering. Clustering by merging Gaussian mixture components. Symmetric and asymmetric discriminant projections for visualisation of the separation of groupings. Cluster validation statistics for distance based clustering including corrected Rand index. Cluster-wise cluster stability assessment. Methods for estimation of the number of clusters: Calinski-Harabasz, Tibshirani and Walther's prediction strength, Fang and Wang's bootstrap stability. Gaussian/multinomial mixture fitting for mixed continuous/categorical variables. Variable-wise statistics for cluster interpretation. DBSCAN clustering. Interface functions for many clustering methods implemented in R, including estimating the number of clusters with kmeans, pam and clara. Modality diagnosis for Gaussian mixtures. For an overview see package?fpc.
Author: Christian Hennig
Maintainer: Christian Hennig

Diff between fpc versions 2.0-3 dated 2010-11-19 and 2.1-4 dated 2012-08-30

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 89 files changed, 1345 insertions(+), 763 deletions(-)

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New package DynClust with initial version 1.0
Package: DynClust
Type: Package
Title: non-parametric denoising and clustering method of noisy images both indexed by time and space
Version: 1.0
Date: 2012-07-31
Author: Yves Rozenholc, Christophe Pouzat, Tiffany Lieury
Maintainer: Tiffany Lieury
Description: The aim of the method is first to denoise each temporal sequence using both the spatial and temporal information contained in the data, and then to cluster them according to their dynamic features. The method is based on the assumption that a finite sequence of noisy images both indexed by time and space is composed of noisy versions of only a limited amount of dynamic features.
Depends: R (>= 2.10)
License: GPL (>= 2)
Packaged: 2012-08-30 12:50:15 UTC; tiffany
Repository: CRAN
Date/Publication: 2012-08-30 15:09:24

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Package rgdal updated to version 0.7-18 with previous version 0.7-16 dated 2012-08-20

Title: Bindings for the Geospatial Data Abstraction Library
Description: Provides bindings to Frank Warmerdam's Geospatial Data Abstraction Library (GDAL) (>= 1.6.0) and access to projection/transformation operations from the PROJ.4 library. The GDAL and PROJ.4 libraries are external to the package, and, when installing the package from source, must be correctly installed first. Both GDAL raster and OGR vector map data can be imported into R, and GDAL raster data and OGR vector data exported. Use is made of classes defined in the sp package. Windows and Mac Intel OS X binaries (including GDAL, PROJ.4 and Expat) are provided on CRAN.
Author: Timothy H. Keitt , Roger Bivand , Edzer Pebesma , Barry Rowlingson
Maintainer: Roger Bivand

Diff between rgdal versions 0.7-16 dated 2012-08-20 and 0.7-18 dated 2012-08-30

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Package rbenchmark updated to version 1.0.0 with previous version 0.3.1 dated 2012-08-13

Title: Benchmarking routine for R
Description: rbenchmark is inspired by the Perl module Benchmark, and is intended to facilitate benchmarking of arbitrary R code. The library consists of just one function, benchmark, which is a simple wrapper around system.time. Given a specification of the benchmarking process (counts of replications, evaluation environment) and an arbitrary number of expressions, benchmark evaluates each of the expressions in the specified environment, replicating the evaluation as many times as specified, and returning the results conveniently wrapped into a data frame.
Author: Wacek Kusnierczyk
Maintainer: Wacek Kusnierczyk

Diff between rbenchmark versions 0.3.1 dated 2012-08-13 and 1.0.0 dated 2012-08-30

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 7 files changed, 206 insertions(+), 113 deletions(-)

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Package evd updated to version 2.3-0 with previous version 2.2-7 dated 2012-07-31

Title: Functions for extreme value distributions
Description: Extends simulation, distribution, quantile and density functions to univariate and multivariate parametric extreme value distributions, and provides fitting functions which calculate maximum likelihood estimates for univariate and bivariate maxima models, and for univariate and bivariate threshold models.
Author: Alec Stephenson. Function fbvpot by Chris Ferro.
Maintainer: Alec Stephenson

Diff between evd versions 2.2-7 dated 2012-07-31 and 2.3-0 dated 2012-08-30

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Package eha updated to version 2.1-2 with previous version 2.0-7 dated 2012-01-05

Title: Event History Analysis
Description: Event history analysis: Sampling of risk sets in Cox regression, selections in the Lexis diagram, bootstrapping. Parametric proportional hazards fitting with left truncation and right censoring for common families of distributions, piecewise constant hazards, and discrete models. AFT regression for left truncated and right censored data. Binary and Poisson regression for clustered data, fixed and random effects with bootstrapping.
Author: Göran Broström
Maintainer: Göran Broström

Diff between eha versions 2.0-7 dated 2012-01-05 and 2.1-2 dated 2012-08-30

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Package ARTIVA updated to version 1.2 with previous version 1.1 dated 2012-07-02

Title: Infer a time-varying DBN network from time series data.
Description: This package generates Reversible Jump MCMC (RJ-MCMC) sampling for approximating the posterior distribution of a time varying regulatory network, under the Auto Regressive TIme VArying (ARTIVA) model (for a detailed description of the algorithm, see Lebre et al. BMC Systems Biology, 2010). Starting from time-course gene expression measurements for a gene of interest (referred to as "target gene") and a set of genes (referred to as "parent genes") which may explain the expression of the target gene, the ARTIVA procedure identifies temporal segments for which a set of interactions occur between the "parent genes" and the "target gene". The time points that delimit the different temporal segments are referred to as changepoints (CP).
Author: S. Lebre and G. Lelandais.
Maintainer: S. Lebre

Diff between ARTIVA versions 1.1 dated 2012-07-02 and 1.2 dated 2012-08-30

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Package SNPRelate updated to version 0.9.7 with previous version 0.9.6 dated 2012-07-22

Title: Parallel Computing Toolset for Genome-Wide Association Studies (GWAS)
Description: A High-performance computing toolset for relatedness and principal component analysis of SNP data
Author: Xiuwen Zheng
Maintainer: Xiuwen Zheng

Diff between SNPRelate versions 0.9.6 dated 2012-07-22 and 0.9.7 dated 2012-08-30

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New package nonparaeff with initial version 0.5-5
Package: nonparaeff
Version: 0.5-5
Date: 2012-08-30
Title: Nonparametric Methods for Measuring Efficiency and Productivity
Author: Dong-hyun Oh , with Dukrok Suh
Maintainer: Dong-hyun Oh
Depends: R (>= 1.8.0), lpSolve, gdata, Hmisc, rms, geometry, psych, pwt
Suggests: gtools
Description: This package contains functions for measuring efficiency and productivity of decision making units (DMUs) under the framework of Data Envelopment Analysis (DEA) and its variations.
License: GPL (>= 2)
URL: http://www.r-project.org
Repository: CRAN
Packaged: 2012-08-30 02:13:50 UTC; arecibo
Date/Publication: 2012-08-30 05:18:42

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Package MARSS updated to version 3.2 with previous version 3.1 dated 2012-07-13

Title: Multivariate Autoregressive State-Space Modeling
Description: The MARSS package provides maximum-likelihood parameter estimation for constrained and unconstrained linear multivariate autoregressive state-space (MARSS) models fit to multivariate time-series data. Fitting is primarily via an Expectation-Maximization (EM) algorithm, although fitting via the BFGS algorithm (using the optim function) is also provided. MARSS models are a class of dynamic linear model (DLM) and vector autoregressive model (VAR) model. Functions are provided for parametric and innovations bootstrapping, Kalman filtering and smoothing, bootstrap model selection criteria (AICb), confidences intervals via the Hessian approximation and via bootstrapping and calculation of auxiliary residuals for detecting outliers and shocks. The user guide shows examples of using MARSS for parameter estimation for a variety of applications, model selection, dynamic factor analysis, outlier and shock detection, and addition of covariates. Type RShowDoc("UserGuide", package="MARSS") at the R command line to open the MARSS user guide. Online workshops (lecture material) at http://faculty.washington.edu/eeholmes/workshops.shtml
Author: Eli Holmes, Eric Ward, and Kellie Wills, NOAA, Seattle, USA
Maintainer: Eli Holmes

Diff between MARSS versions 3.1 dated 2012-07-13 and 3.2 dated 2012-08-30

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More information about MARSS at CRAN
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