[R] CRAN (and crantastic) updates this week

Crantastic cranatic at gmail.com
Mon Mar 15 00:40:12 CET 2010

CRAN (and crantastic) updates this week

New packages

* apcluster (1.0.1)
  Ulrich Bodenhofer

  The apcluster package implements Frey's and Dueck's Affinity
  Propagation clustering in R. The algorithms are analogous to the
  Matlab code published by Frey and Dueck.

* BioPhysConnectoR (1.6-1)
  Franziska Hoffgaard

  Utilities and functions to investigate the relation between
  biomolecular structures, their interactions, and the evolutionary
  information revealed in sequence alignments of these molecules.

* BradleyTerry2 (0.9-1)
  Heather Turner

  Specify and fit the Bradley-Terry model and structured versions

* catnet (1.00.0)
  Nikolay Balov

  A package that handles discrete Bayesian network models and provides
  inference using the frequentist approach

* CAVIAR (0.1-0)
  Cyrille Rathgeber

  Allows processing, visualisation and analysis of data coming from
  cambial activity and wood formation monitoring studies.

* CCMtools (1.0)
  Mathieu Vrac

  This package proposes a clustering method called "Correlation
  Clustering Model" (CCM) based on mixture of canonical correlation
  analysis (CCA). It also provides some tools for cluster analysis.

* clusterCons (0.4)
  Dr. T. Ian Simpson

  clusterCons is a package containing functions that generate robustness
  measures for clusters and cluster membership based on generating
  consensus matrices from bootstrapped clustering experiments in which
  a random proportion of rows of the data set are used in each
  individual clustering. This allows the user to prioritise clusters
  and the members of clusters based on their consistency in this
  regime. The functions allow the user to select several algorithms to
  use in the re-sampling scheme and with any of the parameters that
  the algorithm would normally take.

* dagR (1.0.1)
  Lutz P Breitling

  Functions to draw, manipulate and evaluate directed acyclic graphs.

* DatABEL (0.0-6)
  Yurii Aulchenko

  a package providing interface to C++ FILEVECTOR library facilitating
  analysis of large (giga- to tera-bytes) matrices; matrix storage is
  organized in a way that either columns or rows are quickly
  accessible; primarily aimed to support genome-wide association
  analyzes e.g. using GenABEL and ProbABEL

* DeducerPlugInExample (0.1)
  Ian Fellows

  A example GUI plug-in package to serve as a template.

* DiceDesign (1.0)
  D. Dupuy

  Space-Filling Designs and Uniformity Criteria.

* DiceEval (1.0)
  D. Dupuy

  Estimation, validation and prediction of metamodels (linear models,
  additive models, MARS and PolyMARS)

* DiceKriging (1.0)
  O. Roustant

  Estimation, validation and prediction of kriging models. Important
  functions : km, print.km, plot.km, predict.km.

* DiceOptim (1.0)
  D. Ginsbourger

  Expected Improvement. EGO algorithm. Parallelized versions of EGO:
  Constant Liars.

* digitize (0.0.1-07)
  Timothee Poisot

  Allows to get the data from a graph by providing calibration points

* DistributionUtils (0.1-0)
  David Scott

  This package contains utilities which are of use in the packages I
  have developed for dealing with distributions. Currently these
  packages are GeneralizedHyperbolic, VarianceGamma, and
  SkewHyperbolic. Additional packages are under development. Each of
  these packages requires DistributionUtils. Functionality includes
  sample skewness and kurtosis, log-histogram, moments by integration,
  changing the pint about which a moment is calculated, functions for
  testing distributions using inversion tests and the Massart

* DoseFinding (0.1)
  Bjoern Bornkamp

  The DoseFinding package provides functions for the design and analysis
  of dose-finding experiments (for example pharmaceutical Phase II
  clinical trials). It provides functions for: multiple contrast
  tests, fitting non-linear dose-response models, calculating optimal
  designs and an implementation of the MCPMod methodology. Currently
  only normally distributed homoscedastic endpoints are supported.

* GeneralizedHyperbolic (0.2-0)
  David Scott

  This package provides functions for the hyperbolic and related
  distributions. Density, distribution and quantile functions and
  random number generation are provided for the hyperbolic
  distribution, the generalized hyperbolic distribution, the
  generalized inverse Gaussian distribution and the skew-Laplace
  distribution. Additional functionality is provided for the
  hyperbolic distribution, including fitting of the hyperbolic to

* hergm (1.1-1)
  Michael Schweinberger


* hglm (1.0)
  Lars Ronnegard

  The hglm package is used to fit hierarchical generalized linear
  models. It can be used for linear mixed models and generalized
  linear mixed models with random effects for a variety of links and a
  variety of distributions for both the outcomes and the random
  effects. Fixed effects can also be fitted in the dispersion part of
  the mean model.

* HGLMMM (0.1)
  Marek Molas

  Hierarchical Generalized Linear Models

* isopam (0.9-6)
  Sebastian Schmidtlein

  Isopam clustering algorithm and utilities. Isopam optimizes clusters
  and optionally cluster numbers in a brute force style and aims at an
  optimum separation by a limited number of indicative descriptors
  (typically species).

* MAd (0.2)
  AC Del Re

  This is an integrated meta-analysis package for conducting a research
  synthesis with mean differences data. One of the unique features of
  this package is in its integration of user-friendly functions to
  complete most of the statistical steps involved in a meta-analysis
  with mean differences. It uses recommended procedures as described
  in The Handbook of Research Synthesis and Meta-Analysis (Cooper,
  Hedges, & Valentine, 2009).

* mbmdr (2.0)
  Victor Urrea

  Model Based Multifactor Dimension Reduction proposed by Calle et al.
  (2008) as a dimension reduction method for exploring gene-gene

* minqa (1.1)
  Katharine Mullen

  Derivative-free optimization by quadratic approximation based on an
  interface to Fortran implementations by M. J. D. Powell

* mixOmics (2.6)
  Kim-Anh Le Cao

  The package supplies two efficients methodologies: regularized CCA and
  sparse PLS to unravel relationships between two heterogeneous data
  sets of size (nxp) and (nxq) where the p and q variables are
  measured on the same samples or individuals n. These data may come
  from high throughput technologies, such as omics data (e.g.
  transcriptomics, metabolomics or proteomics data) that require an
  integrative or joint analysis. However, mixOmics can also be applied
  to any other large data sets where p+q>>n. rCCA is a regularized
  version of CCA to deal with the large number of variables. sPLS
  allows variable selection in a one step procedure and two frameworks
  are proposed: regression and canonical analysis. Numerous graphical
  outputs are provided to help interpreting the results.

* MplusAutomation (0.2-3)
  Michael Hallquist

  The MplusAutomation package leverages the flexibility of the R
  language to automate latent variable model estimation and
  interpretation using Mplus, a powerful latent variable modeling
  program developed by Muthen and Muthen (www.statmodel.com).
  Specifically, MplusAutomation provides routines for creating related
  groups of models, running batches of models, and extracting and
  tabulating model parameters and fit statistics.

* mtsc (0.0.1)
  Charlotte Maia

  Place-holder package (roughly speaking an empty package) for finding
  clusters in multivariate timeseries. Full implementation pending.

* ncdf4 (1.0)
  David Pierce

  This package provides a high-level R interface to data files written
  using Unidata's netCDF library (version 4 or earlier), which are
  binary data files that are portable across platforms and include
  metadata information in addition to the data sets. Using this
  package, netCDF files (either version 4 or "classic" version 3) can
  be opened and data sets read in easily. It is also easy to create
  new netCDF dimensions, variables, and files, in either version 3 or
  4 format, and manipulate existing netCDF files. This package
  replaces the former ncdf package, which only worked with netcdf
  version 3 files.  For various reasons the names of the functions
  have had to be changed from the names in the ncdf package.  The old
  ncdf package is still available at the URL given below, if you need
  to have backward compatibility. It should be possible to have both
  the ncdf and ncdf4 packages installed simultaneously without a
  problem. However, the ncdf package does not provide an interface for
  netcdf version 4 files.

* ordinal (2010.03-04)
  Rune Haubo B Christensen

  This package implements likelihood based models for ordinal (ordered
  categorical) data based on cumulative probabilities in the framework
  of cumulative link models. This includes the important proportional
  odds model but also allows for general regression structures for
  location as well as scale of the latent distribution, i.e. additive
  as well as multiplicative structures, structured thresholds
  (cut-points), nominal effects and flexible link functions. Further,
  a range of estimation procedures and a range of auxiliary functions
  are implemented.

* oro.dicom (0.2.4)
  Brandon Whitcher

  Data input/output functions for data that conform to the Digital
  Imaging and Communications in Medicine (DICOM) standard, part of the
  Rigorous Analytics bundle.

* oro.nifti (0.1.3)
  Brandon Whitcher

  Data input/output functions for data that follow either Analyze or
  NIfTI standards, part of the Rigorous Analytics bundle.

* r2lh (0.6)
  Christophe M. Genolini

  generate univariate and bivariate analyses in LaTeX or HTML formats

* random.polychor.pa (1.0)
  Fabio Presaghi

  The Function perform a parallel analysis using simulated polychoric
  correlation matrices. The nth-percentile of the eigenvalues
  distribution obtained from the randomly generated polychoric
  correlation matrices is returned. A plot comparing the two types of
  eigenvalues (real and simulated) will help determine the number of
  real eigenvalues that outperform random data. The function is based
  on the idea that if real data are non-normal and the polychoric
  correlation matrix is needed to perform a Factor Analysis, then the
  Parallel Analysis method used to choose a non-random number of
  factors should also be based on randomly generated polychoric
  correlation matrices and not on Pearson correlation matrices.

* RcmdrPlugin.MAd (0.2)
  AC Del Re

  This is an R-Commander plug-in for the MAd package (Meta-Analysis with
  Mean Differences). This package enables the user to conduct a
  meta-analysis in a menu-driven, graphical user interface environment
  (e.g., SPSS), while having the full statistical capabilities of R
  and the MAd package. The MAd package itself contains a variety of
  useful functions for conducting a research synthesis with mean
  differences data. One of the unique features of the MAd package is
  in its integration of user-friendly functions to complete many of
  the statistical steps involved in a meta-analysis with mean
  differences. It uses recommended procedures as described in The
  Handbook of Research Synthesis and Meta-Analysis (Cooper, Hedges, &
  Valentine, 2009).

* RcppArmadillo (0.1.0)
  Dirk Eddelbuettel and Romain Francois

  R and Armadillo integration using Rcpp Armadillo is a C++ linear
  algebra library aiming towards a good balance between speed and ease
  of use. Integer, floating point and complex numbers are supported,
  as well as a subset of trigonometric and statistics functions.
  Various matrix decompositions are provided through optional
  integration with LAPACK and ATLAS libraries. . A delayed evaluation
  approach is employed (during compile time) to combine several
  operations into one and reduce (or eliminate) the need for
  temporaries. This is accomplished through recursive templates and
  template meta-programming. . This library is useful if C++ has been
  decided as the language of choice (due to speed and/or integration
  capabilities), rather than another language. . This Armadillo / C
  integration provides a nice illustration of the capabilities of the
  Rcpp package for seamless R and C++ integration/

* RcppExamples (0.1.0)
  Dirk Eddelbuettel and Romain Francois

  Examples for Seamless R and C++ integration The Rcpp package contains
  a C++ library that facilitates the integration of R and C++ in
  various ways. This package provides examples.

* Rdsm (1.0.0)
  Norm Matloff

  Provides a threads-like programming environment for R, usable both on
  a multicore machine and across a network of multiple machines.  The
  package gives the illusion of shared memory, again even across
  multiple machines on a network.

* ris (1.0)
  Stephanie Kovalchik

  Importing RIS-formatted file into a list of Bibtex-like references;
  checking for duplications; converting references to citEntry objects

* Rsolnp (1.0-2)
  Alexios Ghalanos

  General Non-linear Optimization Using Augmented Lagrange Multiplier

* saws (0.9-3.1)
  M.P. Fay

  Tests coefficients with sandwich estimator of variance and with small
  samples. Regression types supported are gee, cox regression, and
  conditional logistic regression.

* TreeRank (1.0-0)
  Nicolas Baskiotis

  Implementation of the TreeRank methodology for building tree-based
  ranking rules for bipartite ranking through ROC curve optimization.

* TreeSim (1.0)
  Tanja Stadler

  The package simulates phylogenetic trees under a constant-rate
  birth-death process, conditioned on having a fixed number of final
  tips, or a fixed age, or a fixed age and number of tips. When
  conditioning on the number of final tips, the method allows for
  shifts in rates and mass extinction events during the birth-death
  process. TreeSim further samples appropriately trees with n final
  tips from a set of trees generated by the common sampling algorithm
  stopping when a fixed number m>>n of leaves is first reached. This
  latter method is appropriate for m-tip trees generated under a big
  class of models (details in the bd.gsa.taxa man page).

* tsne (0.1-1)

  A "pure R" implementation of the t-SNE algorithm.

* ttime (1.0)
  Radhakrishnan Nagarajan

  Translate neurodevelopmental event timing across species. Predict
  unknown event timings and investigate phylogenetic proximity by
  hiearchical clustering of the known and predicted event timings.

* UScensus2000blkgrp (0.03)
  Zack W. Almquist

  US Census 2000 Block Group shapefiles and additional demographic data
  from the SF1 100 percent files. This data set contains polygon files
  in lat/lon coordinates and the corresponding demographic data for a
  number of different variables.

* vcdExtra (0.4-1)
  Michael Friendly

  Provides additional data sets, methods and documentation to complement
  the vcd package for Visualizing Categorical Data.

* VizCompX (0.1)
  Neil Diamond

  Nimrod generates a Latin Hypercube Design using the emulator package.
  Based on this design, any function can be evaluated on the design
  points. A generalisation of the Nimrod/O test case is included. A
  Gaussian model can be fit to the data using the mlegp package. The
  resulting surface can be viewed using a wireframe plot with choice
  of viewing and conditioning variables and levels.

* vmv (1.0)
  Waqas Ahmed Malik

  Visualization of Missing Values

* wq (0.2-2)
  Alan Jassby

  Functions to assist in the processing and exploration of data from
  monitoring programs for aquatic ecosystems. The focus is on time
  series data for physical and chemical properties of water, as well
  as the plankton. The package is intended for programs that sample
  approximately monthly at discrete stations.

Updated packages

actuar (1.1-0), agricolae (1.0-9), AlgDesign (1.1-2), analogue
(0.6-23), animation (1.1-0), aroma.affymetrix (1.5.0), aroma.core
(1.5.0), arulesSequences (0.1-9), backtest (0.3-1), bayesclust (3.0),
bcp (2.1.3), betareg (2.2-0), bio.infer (1.2-8), bipartite (1.07),
BoolNet (1.4), BradleyTerry (0.8-8), CADStat (2.2-2), caGUI (0.1-4),
caret (4.33), chemometrics (0.8), cocorresp (0.1-9), compHclust
(1.0-1), conf.design (1.01), corpcor (1.5.6), countrycode (0.4),
cshapes (0.2-3), Deducer (0.2-3), DEoptim (2.0-4), DescribeDisplay
(0.2.2), deSolve (1.7), DiagnosisMed (0.2.3), diffractometry (0.1-02),
DoE.base (0.9-17), dplR (1.2.9), dti (0.9-0), dynGraph (0.99100403),
e1071 (1.5-23), eha (1.2-18), epitools (0.5-5), estout (1.0.1-1),
extracat (1.0-1), extremevalues (2.0), far (0.6-3), farmR (1.1), FD
(1.0-7), flashClust (1.00), flexmix (2.2-5), fmri (1.4-0), forensim
(1.1-4), FrF2 (1.1), ftsa (1.5), fxregime (1.0-0), GAMens (1.1.1),
gcExplorer (0.9-3), GEOmap (1.5-4), GeoXp (1.4.2), GeoXp (1.4.3),
ggplot2 (0.8.7), gmt (1.1-4), gRapHD (0.1.6), gRbase (1.3.4), gsDesign
(2.2-11), gstat (0.9-69), gWidgetsRGtk2 (0.0-62), gWidgetstcltk
(0.0-31), helloJavaWorld (0.0-7), hergm (1.1-1), HiddenMarkov (1.3-1),
hyperdirichlet (1.4-2), ibr (1.2.1), ic.infer (1.1-3), Imap (1.32),
integrativeME (1.2), integrOmics (2.55), interval (0.9-9.6), ipw
(1.0-4), kml (1.1.1), ks (1.6.11), latticeExtra (0.6-9), lda (1.2),
lokern (1.0-9), longitudinalData (0.6.3), MAc (1.0.5), MAc (1.0.6),
MAd (0.2), mboost (2.0-3), mc2d (0.1-7), mclust (3.4.3), MCMCglmm
(2.03), mhsmm (0.3.2), mixAK (0.8), MKmisc (0.6.1), monomvn (1.8-1),
MplusAutomation (0.2-2), MplusAutomation (0.2-3), multcomp (1.1-6),
mvpart (1.3-1), ncvreg (2.0), neuralnet (1.3), nlstools (0.0-10), noia
(0.94), nor1mix (1.1-2), party (0.9-9993), pcaPP (1.8), penalized
(0.9-30), pgirmess (1.4.4), phyclust (0.1-5), picante (1.0-1), plotrix
(2.8-3), plsdof (0.2-0), pmg (0.9-42), portfolio (0.4-5), portfolioSim
(0.2-6), prefmod (0.8-19), PropCIs (0.1-5), PwrGSD (1.16), pyramid
(1.2), qpcR (1.2-6), QRMlib (1.4.5), qvcalc (0.8-5), R.filesets
(0.8.0), R2HTML (2.0.0), R2jags (0.02-02), randomSurvivalForest
(3.6.2), rattle (2.5.24), rbenchmark (0.3), RcmdrPlugin.MAc (1.0.6),
RcmdrPlugin.MAc (1.0.5), Rcpp (0.7.8), Rcpp (0.7.9), relations
(0.5-7), reporttools (1.0.5), REQS (0.8-6), RFLPtools (1.1), RFOC
(1.0-9), RGtk2DfEdit (0.5.4), rimage (0.5-8.1), rms (2.2-0), RQDA
(0.1-9), Rsolnp (1.0-2), rsprng (1.0), RSQLite (0.8-4), RTOMO (1.0-7),
runjags (0.9.6-3), s20x (3.1-7), sandwich (2.2-6), sbgcop (0.975),
sdef (1.5), seacarb (2.3.2), season (0.2-4), seqinr (2.0-8), sfsmisc
(1.0-11), SGP (0.0-5), signal (0.6-1), simecol (0.6-10), simPopulation
(0.1.1), SkewHyperbolic (0.2-0), sm (2.2-4), snowfall (1.83), sp
(0.9-61), spatstat (1.18-0), spBayes (0.1-6), spdep (0.4-59), stab
(0.0.7), statmod (1.4.3), stoichcalc (1.1-1), strucchange (1.4-0),
survey (3.21), SweaveListingUtils (0.4.3), tau (0.0-7), TeachingDemos
(2.6), TeachingSampling (1.4.9), textcat (0.0-2), TGUITeaching
(0.9.6), TGUITeaching (0.9.5), tm (0.5-3), tm.plugin.mail (0.0-2),
tmvtnorm (1.0-2), tnet (2.5), topicmodels (0.0-4), topmodel (0.7.2),
tradeCosts (0.3-1), trio (1.0.14), tsDyn (0.7-22), tseriesChaos
(0.1-10), ttrTests (1.5), unmarked (0.8-3), UScensus2000 (0.07),
UScensus2000add (0.04), UScensus2000cdp (0.03), UScensus2000tract
(0.03), VarianceGamma (0.3-0), vars (1.4-7), vegan (1.17-2),
WMBrukerParser (1.2)

This email provided as a service for the R community by

Like it?  Hate it?  Please let us know: cranatic at gmail.com.

More information about the R-help mailing list