Mon, 02 Mar 2009

Package spatstat updated to version 1.15-0 with previous version 1.14-10 dated 2009-02-03

Author: Adrian Baddeley and Rolf Turner , with substantial contributions of code by Marie-Colette van Lieshout, Rasmus Waagepetersen, Kasper Klitgaard Berthelsen and Dominic Schuhmacher. Additional contributions by Ang Qi Wei, C. Beale, B. Biggerstaff, R. Bivand, F. Bonneu, J.B. Chen, Y.C. Chin, M. de la Cruz, 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, J. Mateu, P. McCullagh, X.C. Mi, J. Moller, L.S. Nielsen, E. Parilov, J. Picka, 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, H. Wang and S. Wong.
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. 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, and pixel images. 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).

Diff between spatstat versions 1.14-10 dated 2009-02-03 and 1.15-0 dated 2009-03-02

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New package mhsmm with initial version 0.1.0
Package: mhsmm
Type: Package
Title: Parameter estimation and prediction for multiple hidden Markov and semi-Markov models
Version: 0.1.0
Date: 2009-01-21
Author: Jared O'Connell with minor contributions from Soren Hojsgaard
Maintainer: Soren Hojsgaard
Description: Parameter estimation and prediction for multiple hidden Markov and semi-Markov models. The times must be equidistant but missing values of the observables are allowed. The observables are allowed to be multivariate. It is possible to have multiple sequences of data. Estimation of the parameters of the models are made using EM--algorithms. Crucial parts of the code is written in C which makes estimation fast. Finally, the package is made so that the user is allow to specify own components of the model.
License: GPL (>= 2)
LazyLoad: yes
Depends: mvtnorm
Packaged: Mon Mar 2 09:23:09 2009; SHD

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Package ltm updated to version 0.9-0 with previous version 0.8-9 dated 2009-01-08

Author: Dimitris Rizopoulos
Title: Latent Trait Models under IRT
Description: Analysis of multivariate dichotomous and polytomous data using latent trait models under the Item Response Theory approach. It includes the Rasch, the Two-Parameter Logistic, the Birnbaum's Three-Parameter, the Graded Response, and the Generalized Partial Credit Models.

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Package fda updated to version 2.1.1 with previous version 2.1.0 dated 2009-01-03

Author: J. O. Ramsay , Hadley Wickham , Spencer Graves , Giles Hooker
Title: Functional Data Analysis
Description: These functions were developed to support functional data analysis as described in Ramsay, J. O. and Silverman, B. W. (2005) Functional Data Analysis. New York: Springer. They were ported from earlier versions in Matlab and S-PLUS. A manual that describes the use of these functions is available in this library. The library also contains a number of the data sets used in the book along with R code for the analyses that produced many of the figures in the book.

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Package Rcpp updated to version 0.6.4 with previous version 0.6.3 dated 2009-01-11

Author: Dirk Eddelbuettel with contributions by Simon Urbanek and David Reiss
Title: Rcpp R/C++ interface package
Description: R/C++ interface classes and examples The Rcpp library maps data types betweeen R and C++, and includes support for R types real, integer, character, vector, matrix, Date, datetime (i.e. POSIXct) at microsecond resolution, data frame, and function. It also supports calling R functions from C++.

Diff between Rcpp versions 0.6.3 dated 2009-01-11 and 0.6.4 dated 2009-03-02

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New package BAS with initial version 0.1
Package: BAS
Version: 0.1
Date: 2009-2-27
Title: Bayesian Model Averaging using Bayesian Adaptive Sampling
Author: Merlise Clyde with contributions from Michael Littman
Maintainer: Merlise Clyde
Depends: R (>= 2.6)
SUGGESTS: MASS
Description: Package for Bayesian Model Averaging in linear models using stochastic or deterministic sampling without replacement from posterior distributions. Prior distributions on coefficients are from Zellner's g-prior or mixtures of g-priors corresponding to the Zellner-Siow Cauchy Priors or the Liang et al hyper-g priors (to appear JASA 2008). Other model selection criterian include AIC and BIC. Sampling probabilities may be updated based on the sampled models.
License: GPL (>= 2)
URL: http://www.r-project.org, http://www.isds.duke.edu/~clyde/BAS
Packaged: Sun Mar 1 19:16:28 2009; clyde

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