Wed, 27 Feb 2013

Package trio updated to version 2.0.1 with previous version 1.9.3 dated 2013-02-04

Title: Testing of SNPs and SNP Interactions in Case-Parent Trio Studies
Description: Testing SNPs and SNP interactions with a genotypic TDT. This package furthermore contains functions for computing pairwise values of LD measures and for identifying LD blocks, as well as functions for setting up matched case pseudo-control genotype data for case-parent trios in order to run trio logic regression, for imputing missing genotypes in trios, for simulating case-parent trios with disease risk dependent on SNP interaction, and for power and sample size calculation in trio data.
Author: Holger Schwender, Qing Li, Christoph Neumann, Ingo Ruczinski
Maintainer: Holger Schwender

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Package inline updated to version 0.3.11 with previous version 0.3.10 dated 2012-10-03

Title: Inline C, C++, Fortran function calls from R
Description: Functionality to dynamically define R functions and S4 methods with in-lined C, C++ or Fortran code supporting .C and .Call calling conventions.
Author: Oleg Sklyar, Duncan Murdoch, Mike Smith, Dirk Eddelbuettel, Romain Francois
Maintainer: Dirk Eddelbuettel

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Package mpoly updated to version 0.0.3 with previous version 0.0.2 dated 2013-02-26

Title: Symbolic computation and more with multivariate polynomials
Description: mpoly allows for the symbolic manipulation of multivariate polynomials in a general and consistent way designed especially for sparse and super sparse polynomials. It also allows for basic differential calculus with multivariate polynomials and Grobner basis calculations from computational algebraic geometry.
Author: David Kahle
Maintainer: David Kahle

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Package frbs updated to version 2.0-0 with previous version 1.0-0 dated 2012-10-29

Title: Fuzzy Rule-based Systems for Classification and Regression Tasks
Description: This package implements functionality and various algorithms to build and use fuzzy rule-based systems (FRBSs). FRBSs are based on the concept of fuzzy sets, proposed by Zadeh in 1965, which aims at representing the reasoning of human experts in a set of IF-THEN rules, to handle real-life problems in, e.g., control, prediction and inference, data mining, bioinformatics data processing, and robotics. FRBSs are also known as fuzzy inference systems and fuzzy models. During the modeling of an FRBS, there are two important steps that need to be conducted: structure identification and parameter estimation. Nowadays, there exists a wide variety of algorithms to generate fuzzy IF-THEN rules automatically from numerical data, covering both steps. Approaches that have been used in the past are, e.g., heuristic procedures, neuro-fuzzy techniques, clustering methods, genetic algorithms, squares methods, etc. This package aims to implement the most widely used standard procedures, thus offering a standard package for FRBS modeling to the R community.
Author: Lala Septem Riza, Christoph Bergmeir, Francisco Herrera, and Jose Manuel Benitez
Maintainer: Christoph Bergmeir

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Package RXMCDA updated to version 1.4.3 with previous version 1.4.2 dated 2012-04-09

Description: The RXMCDA library for the R statistical software allows you to read many XMCDA tags and transform them into R variables which are then usable in your MCDA algorithms written in R. The library also allows to write certain R variables into XML files according to the XMCDA standard.
Author: Patrick Meyer, Sebastien Bigaret.
Maintainer: Patrick Meyer

Diff between RXMCDA versions 1.4.2 dated 2012-04-09 and 1.4.3 dated 2013-02-27

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Package quadrupen updated to version 0.2-1 with previous version 0.2-0 dated 2013-02-26

Title: Sparsity by Worst-Case Quadratic Penalties
Description: This package fits classical sparse regression models with efficient active set algorithms by solving quadratic problems. Also provides a few methods for model selection purpose (cross-validation, stability selection).
Author: Julien Chiquet
Maintainer: Julien Chiquet

Diff between quadrupen versions 0.2-0 dated 2013-02-26 and 0.2-1 dated 2013-02-27

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New package lfstat with initial version 0.2
Package: lfstat
Type: Package
Title: Calculates Low Flow Statistics for daily stream flow data
Version: 0.2
Date: 2013-02-26
Author: Daniel Koffler
Maintainer: Daniel Koffler
Description: The "Manual on Low-flow Estimation and Prediction", published by the World Meteorological Organisation (WMO), gives an idea how to analyse stream flow data focusing on low-flow issues. This packages gives functions to compute the described statistics and produce plots similar to the one in the manual.
License: GPL (>= 2)
LazyLoad: yes
Depends: R (>= 2.10), lattice, lmom, lmomRFA, latticeExtra
Repository: CRAN
Repository/R-Forge/Project: lfstat
Repository/R-Forge/Revision: 24
Repository/R-Forge/DateTimeStamp: 2013-02-26 08:34:47
Date/Publication: 2013-02-27 14:25:53
Packaged: 2013-02-26 11:15:11 UTC; rforge
NeedsCompilation: no

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Package fanplot updated to version 1.3 with previous version 1.2 dated 2013-02-07

Title: Visualisations of sequential probability distributions.
Description: The fanplot package contains a collection of R functions to effectively display plots of sequential distributions such as probabilistic forecasts. The plotting of distributions are based around two functions. The first, pn, calculates the percentiles for a set of sequential distributions over a specified time period. The second, fan, plots the calculated percentiles of the sequential distributions. The resulting plot is a set of coloured polygon, with shadings corresponding to the percentile values.
Author: Guy J. Abel
Maintainer: "Guy J. Abel"

Diff between fanplot versions 1.2 dated 2013-02-07 and 1.3 dated 2013-02-27

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Package robCompositions updated to version 1.6.3 with previous version 1.6.2 dated 2013-01-11

Title: Robust Estimation for Compositional Data.
Description: The package includes methods for imputation of compositional data including robust methods, methods to impute rounded zeros, (robust) outlier detection for compositional data, (robust) principal component analysis for compositional data, (robust) factor analysis for compositional data, (robust) discriminant analysis for compositional data (Fisher rule), robust regression with compositional predictors and (robust) Anderson-Darling normality tests for compositional data as well as popular log-ratio transformations (alr, clr, ilr, and their inverse transformations). In addition, visualisation and diagnostic tools are implemented as well as high and low-level plot functions for the ternary diagram.
Author: Matthias Templ, Karel Hron, Peter Filzmoser
Maintainer: Matthias Templ

Diff between robCompositions versions 1.6.2 dated 2013-01-11 and 1.6.3 dated 2013-02-27

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Package EasyABC updated to version 1.2 with previous version 1.1 dated 2013-01-29

Title: EasyABC: performing efficient approximate Bayesian computation sampling schemes
Description: The package EasyABC enables to launch a series of simulations of a computer code from the R platform, and to retrieve the simulation outputs in an appropriate format for post-processing treatments. Four sequential sampling schemes and three coupled-to-MCMC schemes are implemented.
Author: Franck Jabot, Thierry Faure, Nicolas Dumoullin
Maintainer: Nicolas Dumoulin

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New package earlywarnings with initial version 1.0.32
Package: earlywarnings
Type: Package
Title: Early Warning Signals Toolbox for Detecting Critical Transitions in Timeseries
Version: 1.0.32
Date: 2013-02-18
Author: Vasilis Dakos , with contributions from S.R. Carpenter, T. Cline, L. Lahti
Maintainer: Vasilis Dakos
Description: The Early-Warning-Signals Toolbox provides methods for estimating statistical changes in timeseries that can be used for identifying nearby critical transitions. Based on Dakos et al (2012) Methods for Detecting Early Warnings of Critical Transitions in Time Series Illustrated Using Simulated Ecological Data. PLoS ONE 7(7):e41010
Depends: R (>= 2.14.0), lmtest, nortest, stats, som, Kendall, KernSmooth, moments, fields, spam, tseries, quadprog, akima, ggplot2
LazyLoad: yes
License: GPL (>= 2)
Collate: 'data.R' 'BDSboot.R' 'bdstest_ews.R' 'ch_ews.R' 'ddjnonparam_ews.R' 'earlywarnings-internal.R' 'generic_ews.R' 'sensitivity_ews.R' 'surrogates_ews.R' 'potential_ews.R'
Packaged: 2013-02-27 09:02:36 UTC; vasilisdakos
NeedsCompilation: no
Repository: CRAN
Date/Publication: 2013-02-27 11:15:10

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Package RSKC updated to version 2.2 with previous version 2.1 dated 2013-02-14

Title: Robust sparse K-means
Description: Robust sparse \emph{K}-means.
Author: Yumi Kondo
Maintainer: Yumi Kondo

Diff between RSKC versions 2.1 dated 2013-02-14 and 2.2 dated 2013-02-27

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Package Rcgmin updated to version 2013-02.20 with previous version 2012-8.08 dated 2012-08-08

Title: Conjugate gradient minimization of nonlinear functions with box constraints
Description: Conjugate gradient minimization of nonlinear functions with box constraints incorporating Dai/Yuan update
Author: John C. Nash
Maintainer: John C. Nash

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Package quantreg updated to version 4.95 with previous version 4.94 dated 2012-12-17

Title: Quantile Regression
Description: Quantile regression and related methods.
Author: Roger Koenker
Maintainer: Roger Koenker

Diff between quantreg versions 4.94 dated 2012-12-17 and 4.95 dated 2013-02-27

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Package HDMD updated to version 1.2 with previous version 1.1 dated 2012-09-21

Title: Statistical Analysis Tools for High Dimension Molecular Data (HDMD)
Description: High Dimensional Molecular Data (HDMD) typically have many more variables or dimensions than observations or replicates (D>>N). This can cause many statistical procedures to fail, become intractable, or produce misleading results. This package provides several tools to reduce dimensionality and analyze biological data for meaningful interpretation of results. Factor Analysis (FA), Principal Components Analysis (PCA) and Discriminant Analysis (DA) are frequently used multivariate techniques. However, PCA methods prcomp and princomp do not reflect the proportion of total variation of each principal component. Loadings.variation displays the relative and cumulative contribution of variation for each component by accounting for all variability in data. When D>>N, the maximum likelihood method cannot be applied in FA and the the principal axes method must be used instead, as in of the psych package. The function in this package further allows for a singular covariance matrix by applying a general inverse method to estimate factor scores. Moreover, removes and warns of any variables that are constant, which would otherwise create an invalid covariance matrix. Promax.only further allows users to define rotation parameters during factor estimation. Similar to the Euclidean distance, the Mahalanobis distance estimates the relationship among groups. pairwise.mahalanobis computes all such pairwise Mahalanobis distances among groups and is useful for quantifying the separation of groups in DA. Genetic sequences are composed of discrete alphabetic characters, which makes estimates of variability difficult. MolecularEntropy and MolecularMI calculate the entropy and mutual information to estimate variability and covariability, respectively, of DNA or Amino Acid sequences. Functional grouping of amino acids (Atchley et al 1999) is also available for entropy and mutual information estimation. Mutual information values can be normalized by NMI to account for the background distribution arising from the stochastic pairing of independent, random sites. Alternatively, discrete alphabetic sequences can be transformed into biologically informative metrics to be used in various multivariate procedures. FactorTransform converts amino acid sequences using the amino acid indices determined by Atchley et al 2005.
Author: Lisa McFerrin
Maintainer: Lisa McFerrin

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Package classify updated to version 1.1 with previous version 1.0 dated 2012-08-22

Title: Classification Accuracy and Consistency under IRT models.
Description: IRT classification uses the probability that candidates of a given ability, will answer correctly questions of a specified difficulty to calculate the probability of their achieving every possible score in a test. Due to the IRT assumption of conditional independence (that is every answer given is assumed to depend only on the latent trait being measured) the probability of candidates achieving these potential scores can be expressed by multiplication of probabilities for item responses for a given ability. Once the true score and the probabilities of achieving all other scores have been determined for a candidate the probability of their score lying in the same category as that of their true score (classification accuracy), or the probability of consistent classification in a category over administrations (classification consistency), can be calculated.
Author: Dr Chris Wheadon and Dr Ian Stockford
Maintainer: Dr Chris Wheadon

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Package bc3net updated to version 1.0.1 with previous version 1.0.0 dated 2012-08-29

Title: BC3NET
Description: This package implements the BC3NET algorithm for gene regulatory network inference (de Matos Simoes and Frank Emmert-Streib, Bagging Statistical Network Inference from Large-Scale Gene Expression Data, PLoS ONE 7(3): e33624)
Author: Ricardo de Matos Simoes and Frank Emmert-Streib
Maintainer: Ricardo de Matos Simoes

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Package arm updated to version 1.6-04 with previous version 1.6-03 dated 2013-02-20

Title: Data Analysis Using Regression and Multilevel/Hierarchical Models
Description: R functions for processing lm, glm, mer and polr outputs.
Author: Andrew Gelman [aut], Yu-Sung Su [aut, cre], Masanao Yajima [ctb], Jennifer Hill [ctb], Maria Grazia Pittau [ctb], Jouni Kerman [ctb] and Tian Zheng [ctb]
Maintainer: Yu-Sung Su

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