Planet R

March 11, 2010

Dirk Eddelbuettel

RcppExamples 0.1.0

Version 0.1.0 of RcppExamples, a simple demo package for Rcpp should appear on CRAN some time tomorrow.

As mentioned in the post about release 0.7.8 of Rcpp, Romain and I carved this out of Rcpp itself to provide a cleaner separation of code that implements our R / C++ interfaces (which remain in Rcpp) and code that illustrates how to use it --- which is now in RcppExamples. This also provides an easier template for people wanting to use Rcpp in their packages as it will be easier to wrap one's head around the much smaller RcppExamples package.

A simple example (using the newer API) may illustrate this: 

#include <Rcpp.h>

RcppExport SEXP newRcppVectorExample(SEXP vector) {

    Rcpp::NumericVector orig(vector);			// keep a copy (as the classic version does)
    Rcpp::NumericVector vec(orig.size());		// create a target vector of the same size

    // we could query size via
    //   int n = vec.size();
    // and loop over the vector, but using the STL is so much nicer
    // so we use a STL transform() algorithm on each element
    std::transform(orig.begin(), orig.end(), vec.begin(), sqrt);

    Rcpp::Pairlist res(Rcpp::Named( "result", vec),
                       Rcpp::Named( "original", orig));

    return res;
}

With essentially five lines of code, we provide a function that takes any numeric vector and returns both the original vector and a tranformed version---here by applying a square root operation. Even the looping along the vector is implicit thanks to the generic programming idioms of the Standard Template Library.

Nicer still, even on misuse, exceptions get caught cleanly and we get returned to the R prompt without any explicit coding on the part of the user: 

R> library(RcppExamples)
Loading required package: Rcpp
R> print(RcppVectorExample( 1:5, "new" )) # select new API
$result
[1] 1.000 1.414 1.732 2.000 2.236

$original
[1] 1 2 3 4 5

R> RcppVectorExample( c("foo", "bar"), "new" )
Error in RcppVectorExample(c("foo", "bar"), "new") :
  not compatible with INTSXP
R>

There is also analogous code for the older API in the package, but it is about three times as long, has to loop over the vector and needs to set up the execption handling explicitly.

As of right now, RcppExamples does not document every class but it should already provide a fairly decent start for using Rcpp. And many more actual usage examples are ... in the over two-hundred unit tests in Rcpp.

Update: Now actually showing new rather than classic API.

March 11, 2010 02:46 AM

March 10, 2010

Simon Jackman

Stata Fail

From a recent mailing from Stata (highlighting by me):

DanielRubin.gif

Funnily enough, there is a Daniel Rubin, a bio-informatics person here at Stanford.

by jackman at March 10, 2010 09:45 PM

CRANberries

Package extremevalues updated to version 2.0 with previous version 1.0 dated 2009-12-03

Title: Univariate outlier detection
Description: Detect extreme values in onedimensional data
Author: Mark van der Loo
Maintainer: Mark van der Loo

Diff between extremevalues versions 1.0 dated 2009-12-03 and 2.0 dated 2010-03-10 

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More information about extremevalues at CRAN

March 10, 2010 08:16 PM

Revolutions

Clustering the world's diets

Cluster Analysis is a useful technique for classifying the members of a group (people, events, measurements, etc) into "similar" groups. How "similar" is defined depends on the application, but generally involves looking at a number of attributes of the group. For example, we could cluster people by looking at their skin color, hair type, facial features, perhaps even genetic markers and find that we end up with clusters that are somehow associated with ethnicity. 

Here's a fascinating application of cluster analysis: given data on what the citizens of each country eat (on aggregate), can we cluster the countries of the world into groups with similar diets? That's what Diego Valle did, using the pam (partitioning around medioids) function in R. He presents the six clusters he identifies as a color-coded world map (click to enlarge):

Clustering the worlds diet
Australia gets grouped with North America and much of Europe and Russia as countries whose citizens enjoy a high-calorie diet with all kinds of foods (except not many beans). Countries in yellow have a cereal-rich diet. The diets of the south-east Asian cluster are heavy on fish and rice, but not dairy foods. See Diego's blog for the description of the other clusters, and the R code which created the analysis. The code reads the data directly from a Google Spreadsheet in the cloud, so you can easily run it yourself. It also produces an interesting chart comparing the American diet to that of the rest of the world.

Diego Valle's Food & Fishing Blog: Cluster Analysis of What The World Eats

by David Smith at March 10, 2010 05:44 PM

In case you missed it: February roundup

In case you missed them, here are some articles from last month of particular interest to R users.

We announced the availability on YouTube of "What is R", a 4-part video based on a recent webcast I hosted.

We announced a webinar I hosted on REvolution's debugger for R (a recorded replay is now available).

We linked Salvio Rodrigues at the Open Source blog, who found that Robert Gentelman's appointment to the REvolution Board was "a great impetus ... to look at R again".

We reviewed an application of R to create social networks from 10Gb of phone call data.

We linked to a slide presentation by Ryan Rosario explaining the base graphics system in R.

We updated a previous geographic visualization of an election, illustrating that color scales do matter.

We noted the great lineup for R/Finance 2010 in Chicago (register now!).

We reviewed CRAN packages released and updated in January & February.

We linked to information about Frank Harrell's rms and Hmisc packages, and his upcoming course.

We linked to a story about creating a cluster in Amazon EC2 for parallel computations with the multicore package.

We gave some examples of creating pretty HTML and LaTeX tables with the xtable package.

We showed how to create a mosaic plot (or treemap) in R.

We noted media attention for the R Project, named as 2010 Editor's Choice at Intelligent Enterprise.

We noted that Tex Hull, co-founder of SPSS, has joined the team at REvolution Computing.

We linked to Dirk Eddelbuettel's presentation about the Rcpp interface for C++ code in R.

We linked to some useful tips on speeding up R code with the Rprof function.

We linked to a useful introduction to R's basic object types (vectors, data frames, etc.)

We linked to a Sudoku solver for R (using a different method than the sudoko package)

Other non-R-specific posts in the past month covered a newspaper miscalculating a simple probability, the fate of the employees of the collapsed megabanks and (on a lighter note) Carl Sagan singing again, this time about evolution, and visualizing what happens when you reply-all to an email list.

The R Community Calendar has also been updated.

As always, thanks for the comments and please send any suggestions to me at david@revolution-computing.com. Don't forget you can follow the blog using an RSS reader like Google Reader, or by following me on Twitter (I'm @revodavid). You can find roundups of previous months here.

by David Smith at March 10, 2010 05:19 PM

CRANberries

Package RSQLite updated to version 0.8-4 with previous version 0.8-3 dated 2010-02-11

Title: SQLite interface for R
Description: Database Interface R driver for SQLite. This package embeds the SQLite database engine in R and provides an interface compliant with the DBI package. The source for the SQLite engine (version 3.6.22) is included.
Author: David A. James
Maintainer: Seth Falcon

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More information about RSQLite at CRAN

March 10, 2010 04:16 PM

Package GeoXp updated to version 1.4.2 with previous version 1.4.1 dated 2010-03-10

Title: Interactive exploratory spatial data analysis
Description: GeoXp is a tool for researchers in spatial statistics, spatial econometrics, geography, ecology etc allowing to link dynamically statistical plots with elementary maps. This coupling consists in the fact that the selection of a zone on the map results in the automatic highlighting of the corresponding points on the statistical graph or reversely the selection of a portion of the graph results in the automatic highlighting of the corresponding points on the map. GeoXp includes tools from different areas of spatial statistics including geostatistics as well as spatial econometrics and point processes. Besides elementary plots like boxplots, histograms or simple scatterplos, GeoXp also couples with maps Moran scatterplots, variogram cloud, Lorentz Curves,...In order to make the most of the multidimensionality of the data, GeoXp includes some dimension reduction techniques such as PCA.
Author: Yves Aragon, Thibault Laurent, Lauriane Robidou, Anne Ruiz-Gazen, Christine Thomas-Agnan
Maintainer: Thibault Laurent

Diff between GeoXp versions 1.4.1 dated 2010-03-10 and 1.4.2 dated 2010-03-10 

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More information about GeoXp at CRAN

March 10, 2010 04:16 PM

Package topicmodels updated to version 0.0-4 with previous version 0.0-3 dated 2009-11-06

Title: Topic models
Description: Provides an interface to the C code for Latent Dirichlet Allocation (LDA) models and Correlated Topics Models (CTM) by David M. Blei and the C++ code for fitting LDA models using Gibbs sampling by Xuan-Hieu Phan.
Author: Bettina Gruen and Kurt Hornik
Maintainer: Bettina Gruen

Diff between topicmodels versions 0.0-3 dated 2009-11-06 and 0.0-4 dated 2010-03-10 

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More information about topicmodels at CRAN

March 10, 2010 02:16 PM

Package corpcor updated to version 1.5.6 with previous version 1.5.5 dated 2010-01-14

Title: Efficient Estimation of Covariance and (Partial) Correlation
Description: This package implements a James-Stein-type shrinkage estimator for the covariance matrix, with separate shrinkage for variances and correlations. The details of the method are explained in Sch\"afer and Strimmer (2005) and Opgen-Rhein and Strimmer (2007). The approach is both computationally as well as statistically very efficient, it is applicable to "small n, large p" data, and always returns a positive definite and well-conditioned covariance matrix. In addition to inferring the covariance matrix the package also provides shrinkage estimators for partial correlations, partial variances, and regression coefficients. The inverse of the covariance and correlation matrix can be efficiently computed, and as well as any arbitrary power of the shrinkage correlation matrix. Furthermore, functions are available for fast singular value decomposition, for computing the pseudoinverse, and for checking the rank and positive definiteness of a matrix.
Author: Juliane Schaefer, Rainer Opgen-Rhein, and Korbinian Strimmer.
Maintainer: Korbinian Strimmer

Diff between corpcor versions 1.5.5 dated 2010-01-14 and 1.5.6 dated 2010-03-10 

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More information about corpcor at CRAN

March 10, 2010 02:16 PM

New package DiceOptim with initial version 1.0

Package: DiceOptim
Version: 1.0
Title: Kriging-based optimization for computer experiments
Date: 2009-11-30
Author: D. Ginsbourger, O. Roustant
Maintainer: D. Ginsbourger
Description: Expected Improvement. EGO algorithm. Parallelized versions of EGO: Constant Liars.
Depends: DiceKriging, rgenoud, MASS
License: GPL-3
URL: http://www.dice-consortium.fr/
Packaged: 2010-03-10 12:06:42 UTC; David
Repository: CRAN
Date/Publication: 2010-03-10 14:55:35

More information about DiceOptim at CRAN

March 10, 2010 02:16 PM

New package MplusAutomation with initial version 0.2-1

Package: MplusAutomation
Type: Package
Title: Automating Mplus Model Estimation and Interpretation
Version: 0.2-1
Date: 2010-03-08
Author: Michael Hallquist
Maintainer: Michael Hallquist
Description: 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.
License: LGPL-3
Depends: gsubfn, xtable, tcltk, plyr
LazyLoad: yes
Packaged: 2010-03-10 14:28:03 UTC; hallquistmn
Repository: CRAN
Date/Publication: 2010-03-10 14:55:41

More information about MplusAutomation at CRAN

March 10, 2010 02:16 PM

Package survey updated to version 3.21 with previous version 3.20 dated 2010-02-09

Title: analysis of complex survey samples
Description: Summary statistics, generalised linear models, cumulative link models, Cox models, loglinear models, and general maximum pseudolikelihood estimation for multistage stratified, cluster-sampled, unequally weighted survey samples. Variances by Taylor series linearisation or replicate weights. Post-stratification, calibration, and raking. Two-phase subsampling designs. Graphics. Predictive margins by direct standardization. PPS sampling without replacement. Principal components, factor analysis.
Author: Thomas Lumley
Maintainer: Thomas Lumley

Diff between survey versions 3.20 dated 2010-02-09 and 3.21 dated 2010-03-10 

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More information about survey at CRAN

March 10, 2010 10:16 AM

Package spatstat updated to version 1.18-0 with previous version 1.17-6 dated 2010-02-09

Title: Spatial Point Pattern analysis, model-fitting, simulation, tests
Description: A package for analysing spatial data, mainly Spatial Point Patterns, including multitype/marked points and spatial covariates, in any two-dimensional spatial region. Also supports three-dimensional point patterns. Contains functions for plotting spatial data, exploratory data analysis, model-fitting, simulation, spatial sampling, model diagnostics, and formal inference. Data types include point patterns, line segment patterns, spatial windows, pixel images and tessellations. Point process models can be fitted to point pattern data. Cluster type models are fitted by the method of minimum contrast. Very general Gibbs point process models can be fitted to point pattern data using a function ppm similar to lm or glm. Models may include dependence on covariates, interpoint interaction and dependence on marks. Fitted models can be simulated automatically. Also provides facilities for formal inference (such as chi-squared tests) and model diagnostics (including simulation envelopes, residuals, residual plots and Q-Q plots).
Author: Adrian Baddeley and Rolf Turner , with substantial contributions of code by Marie-Colette van Lieshout, Rasmus Waagepetersen, Kasper Klitgaard Berthelsen, Dominic Schuhmacher and Ege Rubak. Additional contributions by Ang Qi Wei, C. Beale, R. Bernhardt, B. Biggerstaff, R. Bivand, F. Bonneu, J. Burgos, S. Byers, J.B. Chen, Y.C. Chin, B. Christensen, M. de la Cruz, P. Dalgaard, P.J. Diggle, S. Eglen, A. Gault, M. Genton, P. Grabarnik, C. Graf, J. Franklin, U. Hahn, M. Hering, M.B. Hansen, M. Hazelton, J. Heikkinen, K. Hornik, R. Ihaka, R. John-Chandran, D. Johnson, J. Laake, R. Mark, J. Mateu, P. McCullagh, S. Meyer, X.C. Mi, J. Moller, L.S. Nielsen, F. Nunes, E. Parilov, J. Picka, A. Raftery, M. Reiter, B.D. Ripley, B. Rowlingson, J. Rudge, A. Sarkka, K. Schladitz, B.T. Scott, I.-M. Sintorn, M. Spiess, M. Stevenson, P. Surovy, B. Turlach, A. van Burgel, T. Verbeke, A. Villers, H. Wang, H. Wendrock and S. Wong.
Maintainer: Adrian Baddeley

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More information about spatstat at CRAN

March 10, 2010 10:16 AM

Package simecol updated to version 0.6-10 with previous version 0.6-9 dated 2009-09-04

Title: Simulation of ecological (and other) dynamic systems
Description: simecol is an object oriented framework to simulate ecological (and other) dynamic systems. It can be used for differential equations, individual-based (or agent-based) and other models as well. The package helps to organize scenarios (avoids copy and paste) and improves readability and usability of code.
Author: Thomas Petzoldt
Maintainer: Thomas Petzoldt

Diff between simecol versions 0.6-9 dated 2009-09-04 and 0.6-10 dated 2010-03-10 

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More information about simecol at CRAN

March 10, 2010 10:16 AM

Package mboost updated to version 2.0-3 with previous version 2.0-2 dated 2010-03-05

Title: Model-Based Boosting
Description: Functional gradient descent algorithm (boosting) for optimizing general risk functions utilizing component-wise (penalised) least squares estimates or regression trees as base-learners for fitting generalized linear, additive and interaction models to potentially high-dimensional data.
Author: Torsten Hothorn, Peter Buehlmann, Thomas Kneib, Matthias Schmid and Benjamin Hofner
Maintainer: Torsten Hothorn

Diff between mboost versions 2.0-2 dated 2010-03-05 and 2.0-3 dated 2010-03-10 

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More information about mboost at CRAN

March 10, 2010 10:16 AM

Package ibr updated to version 1.2.1 with previous version 1.2 dated 2009-11-16

Title: Iterative Bias Reduction
Description: an R package for multivariate smoothing
Author: Pierre-Andre Cornillon, Nicolas Hengartner, Eric Matzner-Lober
Maintainer: Pierre-Andre Cornillon

Diff between ibr versions 1.2 dated 2009-11-16 and 1.2.1 dated 2010-03-10 

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More information about ibr at CRAN

March 10, 2010 10:16 AM

Package GeoXp updated to version 1.4.1 with previous version 1.4 dated 2009-11-05

Title: Interactive exploratory spatial data analysis
Description: GeoXp is a tool for researchers in spatial statistics, spatial econometrics, geography, ecology etc allowing to link dynamically statistical plots with elementary maps. This coupling consists in the fact that the selection of a zone on the map results in the automatic highlighting of the corresponding points on the statistical graph or reversely the selection of a portion of the graph results in the automatic highlighting of the corresponding points on the map. GeoXp includes tools from different areas of spatial statistics including geostatistics as well as spatial econometrics and point processes. Besides elementary plots like boxplots, histograms or simple scatterplos, GeoXp also couples with maps Moran scatterplots, variogram cloud, Lorentz Curves,...In order to make the most of the multidimensionality of the data, GeoXp includes some dimension reduction techniques such as PCA.
Author: Yves Aragon, Thibault Laurent, Lauriane Robidou, Anne Ruiz-Gazen, Christine Thomas-Agnan
Maintainer: Thibault Laurent

Diff between GeoXp versions 1.4 dated 2009-11-05 and 1.4.1 dated 2010-03-10 

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More information about GeoXp at CRAN

March 10, 2010 10:16 AM

New package Rdsm with initial version 1.0.0

Package: Rdsm
Version: 1.0.0
Author: Norm Matloff
Maintainer: Norm Matloff
Date: 3/5/2010
Title: Threads-Like Environment for R
Description: 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.
LazyLoad: no
License: GPL (>= 2)
Repository: CRAN
Packaged: 2010-03-10 01:44:33 UTC; matloff
Date/Publication: 2010-03-10 10:20:09

More information about Rdsm at CRAN

March 10, 2010 10:16 AM

Dirk Eddelbuettel

Rcpp 0.7.8

Version 0.7.8 of the Rcpp R / C++ interface classes is now on CRAN and in Debian. As of right now. Debian has already built packages for eight more architectures; and CRAN has built the Windows binary. Oh, and cran2deb had Debian packages for 'testing' before I was done with the blog entry.

This is a minor feature release based on a over three weeks of changes that are summarised below in the extract from the NEWS file. Some noteworthy highlights are

  • something that isn't there: we have split most of the example code and their manual pages off into a new package RcppExamples which can now be released given that 0.7.8 is out
  • another new package RcppArmadillo will also be forthcoming shortly: it shows how to use Rcpp with Conrad Sanderson's excellent Armadillo C++ library for linear algebra; this required some internal code changes to seamlessly pass data from R via Rcpp to Armadillo and back;
  • there is a new example fastLm using Armadillo for faster (than lm() or lm.fit()) linear model fits
  • yet more internal improvements to the class hierarchy as detailed below; more support for STL iterators and algorithms;
  • more build fixes; paths with spaces in the name should now be tolerated
  • and last but not least a new introduction / overview vignette based on a just-submitted paper on Rcpp.

The full NEWS entry for this release follows: 

0.7.8   2010-03-09

    o	All vector classes are now generated from the same template class
    	Rcpp::Vector where RTYPE is one of LGLSXP, RAWSXP, STRSXP,
    	INTSXP, REALSXP, CPLXSXP, VECSXP and EXPRSXP. typedef are still 
    	available : IntegerVector, ... All vector classes gain methods 
    	inspired from the std::vector template : push_back, push_front, 
    	erase, insert
    	
    o	New template class Rcpp::Matrix deriving from 
    	Rcpp::Vector. These classes have the same functionality
    	as Vector but have a different set of constructors which checks
    	that the input SEXP is a matrix. Matrix however does/can not
    	guarantee that the object will allways be a matrix. typedef 
    	are defined for convenience: Matrix is IntegerMatrix, etc...
    	
    o	New class Rcpp::Row that represents a row of a matrix
    	of the same type. Row contains a reference to the underlying 
    	Vector and exposes a nested iterator type that allows use of 
    	STL algorithms on each element of a matrix row. The Vector class
    	gains a row(int) method that returns a Row instance. Usage 
    	examples are available in the runit.Row.R unit test file
    	
    o	New class Rcpp::Column that represents a column of a 
    	matrix. (similar to Rcpp::Row). Usage examples are 
    	available in the runit.Column.R unit test file

    o	The Rcpp::as template function has been reworked to be more 
    	generic. It now handles more STL containers, such as deque and 
    	list, and the genericity can be used to implement as for more
    	types. The package RcppArmadillo has examples of this

    o   new template class Rcpp::fixed_call that can be used in STL algorithms
	such as std::generate.

    o	RcppExample et al have been moved to a new package RcppExamples;
        src/Makevars and src/Makevars.win simplified accordingly

    o	New class Rcpp::StringTransformer and helper function 
    	Rcpp::make_string_transformer that can be used to create a function
    	that transforms a string character by character. For example
    	Rcpp::make_string_transformer(tolower) transforms each character
    	using tolower. The RcppExamples package has an example of this.
        
    o	Improved src/Makevars.win thanks to Brian Ripley

    o	New examples for 'fast lm' using compiled code: 
        - using GNU GSL and a C interface
        - using Armadillo (http://arma.sf.net) and a C++ interface
        Armadillo is seen as faster for lack of extra copying

    o	A new package RcppArmadillo (to be released shortly) now serves 
        as a concrete example on how to extend Rcpp to work with a modern 
	C++ library such as the heavily-templated Armadillo library

    o	Added a new vignette 'Rcpp-introduction' based on a just-submitted 
        overview article on Rcpp

As always, even fuller details are in the ChangeLog on the Rcpp page which also leads to the downloads, the browseable doxygen docs and zip files of doxygen output for the standard formats. A local directory has source and documentation too. Questions, comments etc should go to the rcpp-devel mailing list off the R-Forge page

Update: Two links corrected.

March 10, 2010 02:48 AM

Simon Jackman

principal components and image reconstruction

Jeff Lewis at UCLA told me he teaches principal components with an image reconstruction example. This got me inspired to try it myself.

A snapshot appears below, showing how the image quality improves quickly with a relatively small number of principal components. A full, Sweaved write up is here, making use of the biOps package in R.

Montage

by jackman at March 10, 2010 01:47 AM

March 09, 2010

CRANberries

Package randomSurvivalForest updated to version 3.6.2 with previous version 3.6.1 dated 2010-01-27

Title: Ishwaran and Kogalur's Random Survival Forest
Description: Ensemble survival analysis based on a random forest of trees using random inputs.
Author: Hemant Ishwaran , Udaya B. Kogalur
Maintainer: Udaya B. Kogalur

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More information about randomSurvivalForest at CRAN

March 09, 2010 08:16 PM

Package pmg updated to version 0.9-42 with previous version 0.9-41 dated 2009-12-10

Title: Poor Man's GUI
Description: Simple GUI for R using gWidgets.
Author: John Verzani with contributions by Yvonnick Noel
Maintainer: John Verzani

Diff between pmg versions 0.9-41 dated 2009-12-10 and 0.9-42 dated 2010-03-09 

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More information about pmg at CRAN

March 09, 2010 08:16 PM

Package ks updated to version 1.6.11 with previous version 1.6.10 dated 2010-02-24

Title: Kernel smoothing
Description: Kernel density estimators and kernel discriminant analysis for multivariate data
Author: Tarn Duong
Maintainer: Tarn Duong

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More information about ks at CRAN

March 09, 2010 08:16 PM

Package gWidgetsRGtk2 updated to version 0.0-62 with previous version 0.0-61 dated 2010-03-07

Title: Toolkit implementation of gWidgets for RGtk2
Description: Port of gWidgets API to RGtk2
Author: Michael Lawrence, John Verzani
Maintainer: John Verzani

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March 09, 2010 08:16 PM

Package Rcpp updated to version 0.7.8 with previous version 0.7.7 dated 2010-02-14

Title: Rcpp R/C++ interface package
Description: Seamless R and C++ integration The Rcpp package contains a C++ library that facilitates the integration of R and C++ in various ways. R data types (SEXP) are matched to C++ objects in a class hierarchy. All R types are supported (vectors, functions, environment, etc ...) and each type is mapped to a dedicated class. For example, numeric vectors are represented as instances of the Rcpp::NumericVector class, environments are represented as instances of Rcpp::Environment, functions are represented as Rcpp::Function, etc ... The underlying C++ library also offers the Rcpp::wrap function which is a templated function that transforms an arbitrary object into a SEXP. This makes it straightforward to implement C++ logic in terms of standard C++ types such as STL containers and then wrap them when they need to be returned to R. Internally, wrap uses advanced template meta programming techniques and currently supports : primitive types (bool, int, double, size_t, Rbyte, Rcomplex, std::string), STL containers (e.g std::vector) where T is wrappable, STL maps (e.g std::map) where T is wrappable, and arbitrary types that support implicit conversion to SEXP. The reverse conversion (from R to C++) is performed by the Rcpp::as function template offering a similar degree of flexibility. The package also contains a set of classes---which we call the `classic Rcpp API'---that were provided in an earlier API for R and C++ integration. Due to its continued use, the classic API is retained and will be supported for the foreseable future. The classic API includes support for R types real, integer, character, vector, matrix, Date, datetime (i.e. POSIXct) at microsecond resolution, data frame, and function. Transfer to and from simple or complex SEXP objects is made easy thanks to automatic conversion made possible by C++ template conversion. Calling R functions from C++ is also supported. C++ code can be 'inlined' by using the 'inline' package which will create a C++ function and compile, link and load it given the 'inlined' character argument which makes C++ integration very easy. Several examples are included, and over 150 unit tests provide addtional usage examples.
Author: Dirk Eddelbuettel and Romain Francois, with contributions by Simon Urbanek and David Reiss; based on code written during 2005 and 2006 by Dominick Samperi
Maintainer: Dirk Eddelbuettel and Romain Francois

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More information about Rcpp at CRAN

March 09, 2010 08:16 PM

New package clusterCons with initial version 0.4

Package: clusterCons
Type: Package
Version: 0.4
Title: Calculate the consensus clustering result from re-sampled clustering experiments with the option of using multiple algorithms and parameter
Date: 2010-03-06
Author: Dr. T. Ian Simpson, University of Edinburgh
Maintainer: Dr. T. Ian Simpson
Depends: methods,cluster
Suggests: lattice,grid
Enhances: cluster
Description: 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.
License: GPL
LazyLoad: yes
URL: http://sourceforge.net/projects/clustercons/
Packaged: 2010-03-09 14:19:15 UTC; isimpson
Repository: CRAN
Date/Publication: 2010-03-09 19:28:04

More information about clusterCons at CRAN

March 09, 2010 08:16 PM

Package DiagnosisMed updated to version 0.2.3 with previous version 0.2.2.2 dated 2009-08-25

Title: Diagnostic test accuracy evaluation for medical professionals.
Description: DiagnosisMed is a package to analyze data from diagnostic test accuracy evaluating health conditions. It is being built to be used by health professionals. This package is able to estimate sensitivity and specificity from categorical and continuous test results including some evaluations of indeterminate results, or compare different categorical tests, and estimate reasonble cut-offs of tests and display it in a way commonly used by health professionals. No graphical interface is avalible yet. Partners are most welcome.
Author: Pedro Brasil
Maintainer: Pedro Brasil

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More information about DiagnosisMed at CRAN

March 09, 2010 08:16 PM

Package pcaPP updated to version 1.8 with previous version 1.7 dated 2009-07-18

Title: Robust PCA by Projection Pursuit
Description: Robust PCA by Projection Pursuit
Author: Peter Filzmoser Heinrich Fritz Klaudius Kalcher
Maintainer: Peter Filzmoser

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More information about pcaPP at CRAN

March 09, 2010 12:16 PM

Package monomvn updated to version 1.8-1 with previous version 1.8 dated 2010-01-14

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 the lasso (double-exponential) and Normal-Gamma priors, and Student-t errors. 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), and ridge regression with model selection via Reversible Jump, and student-t errors (from Geweke) is also provided
Author: Robert B. Gramacy
Maintainer: Robert B. Gramacy

Diff between monomvn versions 1.8 dated 2010-01-14 and 1.8-1 dated 2010-03-09 

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More information about monomvn at CRAN

March 09, 2010 12:16 PM

Package chemometrics updated to version 0.8 with previous version 0.7 dated 2010-03-04

Title: Multivariate Statistical Analysis in Chemometrics
Description: This package is the R companion to the book "Introduction to Multivariate Statistical Analysis in Chemometrics" written by K. Varmuza and P. Filzmoser (2009)
Author: P. Filzmoser and K. Varmuza
Maintainer: P. Filzmoser

Diff between chemometrics versions 0.7 dated 2010-03-04 and 0.8 dated 2010-03-09 

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More information about chemometrics at CRAN

March 09, 2010 12:16 PM

Package BradleyTerry updated to version 0.8-8 with previous version 0.8-7 dated 2008-07-11

Title: Bradley-Terry Models -- this package is now deprecated in favour of 'BradleyTerry2'
Description: Specify and fit the Bradley-Terry model and structured versions
Author: David Firth
Maintainer: David Firth

Diff between BradleyTerry versions 0.8-7 dated 2008-07-11 and 0.8-8 dated 2010-03-09 

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More information about BradleyTerry at CRAN

March 09, 2010 12:16 PM

Package spBayes updated to version 0.1-6 with previous version 0.1-5 dated 2010-01-08

Title: Univariate and Multivariate Spatial Modeling
Description: spBayes fits univariate and multivariate models with Markov chain Monte Carlo (MCMC).
Author: Andrew O. Finley , Sudipto Banerjee , Bradley P. Carlin
Maintainer: Andrew O. Finley

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More information about spBayes at CRAN

March 09, 2010 08:16 AM

Package sp updated to version 0.9-61 with previous version 0.9-60 dated 2010-02-15

Title: classes and methods for spatial data
Description: A package that provides classes and methods for spatial data. The classes document where the spatial location information resides, for 2D or 3D data. Utility functions are provided, e.g. for plotting data as maps, spatial selection, as well as methods for retrieving coordinates, for subsetting, print, summary, etc.
Author: Edzer Pebesma , Roger Bivand and others
Maintainer: Edzer Pebesma

Diff between sp versions 0.9-60 dated 2010-02-15 and 0.9-61 dated 2010-03-09 

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More information about sp at CRAN

March 09, 2010 08:16 AM

Package rsprng updated to version 1.0 with previous version 0.4 dated 2008-06-08

Title: R interface to SPRNG (Scalable Parallel Random Number Generators)
Description: Provides interface to SPRNG 2.0 APIs, and examples and documentation for its use.
Author: Na (Michael) Li
Maintainer: Na (Michael) Li

Diff between rsprng versions 0.4 dated 2008-06-08 and 1.0 dated 2010-03-09 

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More information about rsprng at CRAN

March 09, 2010 08:16 AM

Package sbgcop updated to version 0.975 with previous version 0.95 dated 2007-03-09

Title: Semiparametric Bayesian Gaussian copula estimation and imputation
Description: This package estimates parameters of a Gaussian copula, treating the univariate marginal distributions as nuisance parameters as described in Hoff(2007). It also provides a semiparametric imputation procedure for missing multivariate data.
Author: Peter Hoff
Maintainer: Peter Hoff

Diff between sbgcop versions 0.95 dated 2007-03-09 and 0.975 dated 2010-03-09 

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More information about sbgcop at CRAN

March 09, 2010 08:16 AM

Package mc2d updated to version 0.1-7 with previous version 0.1-6 dated 2009-09-12

Title: Tools for Two-Dimensional Monte-Carlo Simulations
Description: Various distributions and utilities to ease the use of R to build and study Two-Dimensional Monte-Carlo simulations
Author: Regis Pouillot , Marie Laure Delignette-Muller and Jean-Baptiste Denis
Maintainer: Regis Pouillot

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More information about mc2d at CRAN

March 09, 2010 08:16 AM

Package far updated to version 0.6-3 with previous version 0.6-2 dated 2007-10-02

Title: Modelization for Functional AutoRegressive processes
Description: Modelizations and previsions functions for Functional AutoRegressive processes using nonparametric methods: functional kernel, estimation of the covariance operator in a subspace, ...
Author: Damon Julien Guillas Serge
Maintainer: Damon Julien

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More information about far at CRAN

March 09, 2010 08:16 AM

Package FD updated to version 1.0-7 with previous version 1.0-5 dated 2009-11-30

Title: Measuring functional diversity (FD) from multiple traits, and other tools for functional ecology
Description: FD is a package to compute different multidimensional FD indices. It implements a distance-based framework to measure FD that allows any number and type of functional traits, and can also consider species relative abundances. It also contains other useful tools for functional ecology.
Author: Etienne Laliberté, Bill Shipley
Maintainer: Etienne Laliberté

Diff between FD versions 1.0-5 dated 2009-11-30 and 1.0-7 dated 2010-03-09 

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More information about FD at CRAN

March 09, 2010 08:16 AM

Package CADStat updated to version 2.2-2 with previous version 2.1-21 dated 2009-06-29

Title: Provides a GUI to several statistical methods useful for causal assessment.
Description: Using JGR, provides a GUI to several statistical methods - scatterplot, boxplot, linear regression, generalized linear regression, quantile, regression, conditional probability calculations, and regression trees.
Author: Lester Yuan, Tom Stockton, Doug Bronson, Pasha Minallah, and Mark Fitzgerald
Maintainer: Lester Yuan

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March 09, 2010 08:16 AM

Revolutions

White House taps Edward Tufte to explain the stimulus

Edward Tufte, a pioneer of effective data visualization (and a personal hero) has just been appointed by the White House to the Recovery Independent Advisory Panel. This panel advises The Recovery Accountability and Transparency Board, whose job is to track and explain $787 billion in recovery stimulus funds. Tufte explains:

I'm doing this because I like accountability and transparency, and I believe in public service. And it is the complete opposite of everything else I do. Maybe I'll learn something. The practical consequence is that I will probably go to Washington several days each month, in addition to whatever homework and phone meetings are necessary.

This is a great move -- while the effects of the stimulus can be debated (and have been ad nauseam), there's no question that the Administration has had trouble explaining the facts amidst all the noise. It's possible that Tufte's had some behind-the-scenes influence already: as Fast Company points out this recent chart has been more successful than many recent attempts to explain the benefits of the stimulus.

Obama_Stimulus_Infographic
 

Sure, using changes in unemployment instead of absolute numbers certainly belies an agenda, but at least it is clear, meaningful, and based on facts. 

by David Smith at March 09, 2010 12:22 AM

March 08, 2010

Revolutions

Open Source is Opening Data to Predictive Analytics

This article by REvolution Computing CEO Norman Nie is crossposted from the Future of Open Source Forum.

The R Project: despite there being over 2 million users of this open-source language for statistical data analysis, you might not have heard of it ... yet. You might have seen this feature in the New York Times last year, and you might have heard how REvolution Computing is enhancing and supporting R for commercial use. Because what was once a secret of drug-development statisticians at pharmaceutical companies, quants on Wall Street, and PhD-level statistical researchers around the globe (not to mention pioneers at Web 2.0 companies like Google and Facebook) is suddenly becoming mainstream. The reason? The perfect storm of a deluge of data, open-source technology, and the rise of predictive analytics.

Predictive analytics -- the process of being able to infer meaningful relationships and predictions from vast quantities of data -- is disrupting industries in every sector. You've probably seen the impact of predictive analytics yourself: ever been surprised by Amazon apparently "reading your mind" on a suggested purchase, or by LinkedIn being able to figure out who you know, but aren't yet connected with? That's predictive analytics in action. By applying advanced statistical models to data, product designers, marketers, sales organizations -- basically, anyone who needs to understand the present or predict the future -- are able to draw value from the data they've collected like never before.

Predictive analytics are only possible with data -- lots of data. Just last week, the Economist published a nine-part special report on the Data Deluge. Companies like Nestlé and Walmart are collecting reams of data on individual products and consumers. And given that Nestlé (to take just one example) has more than 100,000 products in 200 countries, we're talking about huge amounts of data being collected.

The world has largely solved the problem of how to collect and store these vast quantities of data -- see David McFarlane's post for a great review of the impact of FOSS here. But the real impact of analyzing these data sets is only just now being felt routinely. It truly is a revolution: the information that can be teased out of these data is shaking many industries to their core. This quote from the Economist special report sums it up well:

“Revolutions in science have often been preceded by revolutions in measurement,” says Sinan Aral, a business professor at New York University. Just as the microscope transformed biology by exposing germs, and the electron microscope changed physics, all these data are turning the social sciences upside down.

Open Source software is playing a key role in this revolution. A noted analyst recently wrote that the most important factor influencing the spread of predictive analytics is the growing popularity of R. And in the Economist's special report, the combination of R and Hadoop received special attention:

A free programming language called R lets companies examine and present big data sets, and free software called Hadoop now allows ordinary PCs to analyse huge quantities of data that previously required a supercomputer. It does this by parcelling out the tasks to numerous computers at once. This saves time and money. For example, the New York Times a few years ago used cloud computing and Hadoop to convert over 400,000 scanned images from its archives, from 1851 to 1922. By harnessing the power of hundreds of computers, it was able to do the job in 36 hours.

This revolution fills me with some pride: I started pushing for broad adoption of data analytics as a crucial element in every aspect of science and business decision-making some 40 years ago, when I created SPSS (now part of IBM). The revolution began in scientific practice and now open source R (co-created by REvolution board member Robert Gentleman) represents its future. Today, all of the Fortune 500 companies use R for their data analyses. It’s used in life sciences, financial services, defense technology and other large industries requiring high performance analytical computation. 

In the coming months and years, I predict that open-source software will continue to be the driving force in analytical innovation. Open-source platforms like Hadoop, coupled with innovations in open-source file-systems, are able to adapt to the rapidly-evolving data storage and processing requirements. And it's open-source environments like R, with its world-wide community of researchers collaborating to push the boundaries of statistical analytics, that are most likely provide the novel predictive techniques required to tease yet more accurate predictions from these huge information-age datasets. Tie that with the backing of a commercial company to provide the scalability, usability, and integration into Web-based systems that businesses require to deploy predictive analytics, and you've truly got a REvolution in the making.

by David Smith at March 08, 2010 11:57 PM

CRANberries

Package vegan updated to version 1.17-2 with previous version 1.17-1 dated 2010-02-18

Title: Community Ecology Package
Description: Ordination methods, diversity analysis and other functions for community and vegetation ecologists.
Author: Jari Oksanen, F. Guillaume Blanchet, Roeland Kindt, Pierre Legendre, R. B. O'Hara, Gavin L. Simpson, Peter Solymos, M. Henry H. Stevens, Helene Wagner
Maintainer: Jari Oksanen

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March 08, 2010 06:16 PM

Package trio updated to version 1.0.14 with previous version 1.0.13 dated 2010-03-04

Title: Processing and Simulating Genotype Data for Trio Logic Regression
Description: Set up matched case-pseudo controls genotypes data for trios in order to run trio logic regreesion, to impute missing genotypes in trios, or to simulate case-parent trios with disease risk dependent on SNP-SNP interaction. This package furthermore contains functions for computing the values of pairwise LD measures and for identifying LD blocks.
Author: Qing Li, Holger Schwender
Maintainer: Qing Li

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March 08, 2010 06:16 PM

New package hglm with initial version 1.0

Package: hglm
Type: Package
Title: hglm is used to fit hierarchical generalized linear models.
Version: 1.0
Date: 13-02-2010
Author: M. Alam, L. Ronnegard, X. Shen.
Maintainer: Lars Ronnegard
Description: 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.
License: Unlimited
LazyLoad: yes
Packaged: 2010-03-08 18:28:10 UTC; Andy X.Shen
Repository: CRAN
Date/Publication: 2010-03-08 19:01:09

More information about hglm at CRAN

March 08, 2010 06:16 PM

New package digitize with initial version 0.0.1-07

Package: digitize
Version: 0.0.1-07
Date: 2010-06-03
Title: digitize : a plot digitizer in R
Author: Timothee Poisot
Maintainer: Timothee Poisot
Depends: R (>= 2.2.0), ReadImages
Description: Allows to get the data from a graph by providing calibration points
License: GPL (>= 2)
URL: http://www.timotheepoisot.fr/r
Repository: CRAN
Repository/R-Forge/Project: scian
Repository/R-Forge/Revision: 47
Date/Publication: 2010-03-08 19:01:05
Packaged: 2010-03-06 21:39:55 UTC; rforge

More information about digitize at CRAN

March 08, 2010 06:16 PM

Revolutions

Chilean earthquake: impact of the tsunami

The National Oceanic and Atmospheric Administration (NOAA) has a page with some interesting information about last week's earthquake in Chile, but what really stood out for me was this chart of the predicted wave heights around the globe resulting from the associated tsunami:

Waveheights 

Click to enlarge: it's a fascinating chart. Although labelled a forecast, from the explanations on the page it appears to be based on observed wave heights at various monitoring stations (with model-based interpolations between them, I assume). This really was a hemispheric event, with impacts around the entire Pacific basin. Clearly though, the impact on the Chilean coast was extreme. Unfortunately NOAA doesn't have a similar chart for the devastating Boxing Day 2004 tsunami; it would be interesting to compare them. (By the way, although you can easily create charts like this in R, I'm not sure whether R was used for this one or not.)

West Coast/Alaska Tsunami Warning Center, NOAA/NWS: Offshore Maule, Chile Tsunami of 27 February 2010

by David Smith at March 08, 2010 05:19 PM

CRANberries

Package ipw updated to version 1.0-4 with previous version 1.0-3 dated 2010-03-05

Title: Estimate inverse probability weights.
Description: Estimate inverse probability weights. These are typically used to perform inverse probability weighting (IPW) to fit a marginal structural model (MSM), to estimate causal effects from observational data. Both data from point treatment situations and longitudinal studies can be used.
Author: Willem M. van der Wal
Maintainer: Willem M. van der Wal

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March 08, 2010 04:16 PM

Package dynGraph updated to version 0.99100403 with previous version 0.99070509 dated 2009-05-17

Title: Interactive visualization of dataframes and factorial planes
Description: Interactive visualization of dataframes and factorial planes
Author: Sebastien Le, Julien Durand
Maintainer: Sebastien Le

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March 08, 2010 04:16 PM

Package bio.infer updated to version 1.2-8 with previous version 1.2-7 dated 2010-02-28

Title: Predict environmental conditions from biological observations
Description: Imports benthic count data, reformats this data, and computes environmental inferences from this data.
Author: Lester L. Yuan
Maintainer: Lester L. Yuan

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March 08, 2010 04:16 PM

New package DoseFinding with initial version 0.1

Package: DoseFinding
Type: Package
Title: Planning and Analyzing Dose Finding experiments
Version: 0.1
Date: 2010-08-03
Author: Bjoern Bornkamp, Jose Pinheiro, Frank Bretz
Depends: lattice, mvtnorm, numDeriv, R (>= 2.4.1)
Suggests: multcomp, Rsolnp
Maintainer: Bjoern Bornkamp
Description: 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.
License: GPL-3
LazyLoad: yes
Packaged: 2010-03-08 13:32:46 UTC; bornkamp
Repository: CRAN
Date/Publication: 2010-03-08 15:38:59

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March 08, 2010 04:16 PM

Package relations updated to version 0.5-7 with previous version 0.5-6 dated 2010-02-10

Title: Data Structures and Algorithms for Relations
Description: Data structures and algorithms for k-ary relations with arbitrary domains, featuring relational algebra, predicate functions, and fitters for consensus relations.
Author: Kurt Hornik and David Meyer
Maintainer: Kurt Hornik

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March 08, 2010 10:16 AM

Package lda updated to version 1.2 with previous version 1.1 dated 2009-09-29

Title: Collapsed Gibbs sampling methods for topic models.
Description: This package implements latent Dirichlet allocation (LDA) and related models. This includes (but is not limited to) sLDA, corrLDA, and the mixed-membership stochastic blockmodel. Inference for all of these models is implemented via a fast collapsed Gibbs sampler writtten in C. Utility functions for reading/writing data typically used in topic models, as well as tools for examining posterior distributions are also included.
Author: Jonathan Chang
Maintainer: Jonathan Chang

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March 08, 2010 10:16 AM

New package catnet with initial version 1.00.0

Package: catnet
Title: catnet: Categorical Bayesian Network Inference
Version: 1.00.0
Author: Nikolay Balov, Peter Salzman
Description: A package that handles discrete Bayesian network models and provides inference using the frequentist approach
Maintainer: Nikolay Balov , Peter Salzman
License: GPL (>= 2)
Depends: R (>= 2.9.0), methods
Imports: methods, stats, tools, utils
Suggests: igraph, graph, snow
Collate: catnet.class.R catnet.def.R graph2catnet.R catnet.dags.R catnet.probs.R catnet.joint.prob.R catnet.marginal.prob.R catnet.samples.R catnet.infer.R catnet.dist.R catnet.find.R catnet.search.R catnet.predict.R catnet.chisq.R zzz.R
LazyLoad: yes
Repository: CRAN
Date/Publication: 2010-03-08 10:34:48
Packaged: 2010-03-05 16:14:51 UTC; root

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March 08, 2010 10:16 AM

Package animation updated to version 1.1-0 with previous version 1.0-10 dated 2009-12-02

Title: Demonstrate Animations in Statistics
Description: This package consists of various functions for animations in statistics, covering many areas such as probability theory, mathematical statistics, multivariate statistics, nonparametric statistics, sampling survey, linear models, time series, computational statistics, data mining and machine learning. These functions might be of help in teaching statistics and data analysis.
Author: Yihui Xie
Maintainer: Yihui Xie

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March 08, 2010 10:16 AM

March 07, 2010

CRANberries

Package arulesSequences updated to version 0.1-9 with previous version 0.1-8 dated 2009-06-15

Title: Mining frequent sequences
Description: Add-on for arules to handle and mine frequent sequences. Provides interfaces to the C++ implementation of cSPADE by Mohammed J. Zaki.
Author: Christian Buchta and Michael Hahsler
Maintainer: Christian Buchta

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March 07, 2010 06:16 PM

Package REQS updated to version 0.8-6 with previous version 0.8-5 dated 2009-11-19

Title: R/EQS Interface
Description: This package contains the function run.eqs() which calls an EQS script file, executes the EQS estimation, and, finally, imports the results as R objects. These two steps can be performed separately: call.eqs() calls and executes EQS, whereas read.eqs() imports existing EQS outputs as objects into R.
Author: Patrick Mair, Eric Wu
Maintainer: Eric Wu

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March 07, 2010 06:16 PM

New package MAd with initial version 0.1

Package: MAd
Type: Package
Title: Meta-Analysis with Mean Differences
Version: 0.1
Date: 2010-03-07
Author: AC Del Re & William T. Hoyt
Maintainer: AC Del Re
Description: This is an integrated meta-analysis package for conducting a research synthesis with mean difference data. One of the unique features of this package is in its integration of user-friendly functions to complete all 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).
Depends: R (>= 2.10.1), plyr, ggplot2
License: GPL-2
Packaged: 2010-03-07 18:18:35 UTC; User
Repository: CRAN
Date/Publication: 2010-03-07 18:41:41

More information about MAd at CRAN

March 07, 2010 06:16 PM

Package vcdExtra updated to version 0.4-1 with previous version 0.4-0 dated 2010-02-28

Title: vcd additions
Description: Provides additional data sets, methods and documentation to complement the vcd package for Visualizing Categorical Data.
Author: Michael Friendly with Heather Turner, David Firth and Achim Zeileis
Maintainer: Michael Friendly

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 man/Dyke.Rd                            |   14 +++++-
 man/Heckman.Rd                         |   45 +++++++++++++++++----
 man/modFit.Rd                          |only
 man/mosaic.glm.Rd                      |   30 ++++++++++----
 man/vcdExtra-package.Rd                |    4 -
 33 files changed, 254 insertions(+), 125 deletions(-)

More information about vcdExtra at CRAN

March 07, 2010 04:16 PM

Package rbenchmark updated to version 0.3 with previous version 0.2 dated 2009-03-27

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 0.2 dated 2009-03-27 and 0.3 dated 2010-03-07 

 DESCRIPTION              |    8 ++++----
 R/benchmark.R            |   18 ++++++++++++------
 man/benchmark-package.Rd |    4 ++--
 man/benchmark.Rd         |    8 +++++---
 4 files changed, 23 insertions(+), 15 deletions(-)

More information about rbenchmark at CRAN

March 07, 2010 04:16 PM

Package rattle updated to version 2.5.24 with previous version 2.5.23 dated 2010-03-04

Title: A graphical user interface for data mining in R using Gnome
Description: Rattle (the R Analytic Tool To Learn Easily) provides a Gnome (RGtk2) based interface to R functionality for data mining. The aim is to provide a simple and intuitive interface that allows a user to quickly load data from a CSV file (or via ODBC), transform and explore the data, build and evaluate models, and export models as PMML (predictive modelling markup language) or as scores. All of this with knowing little about R. All R commands are logged and commented through the log tab and so available to the user as a script file or as an aide to the user to interact directly with R itself. Rattle also exports a number of utility functions and the graphical user interface, invoked as rattle(), does not need to be run to deploy these.
Author: Graham Williams
Maintainer: Graham Williams

Diff between rattle versions 2.5.23 dated 2010-03-04 and 2.5.24 dated 2010-03-07 

 DESCRIPTION                        |    8 
 R/data.R                           |    7 
 R/evaluate.R                       |  165 +++--
 R/help.R                           | 1031 ++++++++++++++++++-------------------
 R/rattle.R                         |    8 
 data/weatherAUS.RData              |binary
 inst/ChangeLog                     |   14 
 inst/doc/rattle.pdf                |binary
 inst/etc/rattle.glade              |   65 +-
 inst/po/de/LC_MESSAGES/R-rattle.mo |binary
 inst/po/es/LC_MESSAGES/R-rattle.mo |binary
 inst/po/ja/LC_MESSAGES/R-rattle.mo |binary
 12 files changed, 702 insertions(+), 596 deletions(-)

More information about rattle at CRAN

March 07, 2010 04:16 PM

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