Thu, 26 Apr 2012

Package rfPermute updated to version 1.1 with previous version 1.0.1 dated 2011-08-24

Title: Estimate permutation p-values for importance metrics.
Description: Estimate significance of importance metrics for a Random Forest model by permuting the response variable. Produces null distribution of importance metrics for each predictor variable and p-value of observed.
Author: Eric Archer
Maintainer: Eric Archer

Diff between rfPermute versions 1.0.1 dated 2011-08-24 and 1.1 dated 2012-04-26

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Package pcalg updated to version 1.1-5 with previous version 1.1-4 dated 2011-05-09

Title: Estimation of CPDAG/PAG and causal inference using the IDA algorithm
Description: Standard and robust estimation of the equivalence class of a Directed Acyclic Graph (DAG) via the PC-Algorithm. The equivalence class is represented by its (unique) Completete Partially Directed Acyclic Graph (CPDAG). Furthermore, a PAG instead of a CPDAG can be estimated if latent variables and/or selection variables are assumed to be present. FCI and RFCI are available for estimating PAGs. Functions for causal inference using the IDA algorithm (based on do-calculus of Judea Pearl) are provided for CPDAGs.
Author: Markus Kalisch, Martin Maechler, Diego Colombo
Maintainer: Markus Kalisch

Diff between pcalg versions 1.1-4 dated 2011-05-09 and 1.1-5 dated 2012-04-26

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Package party updated to version 1.0-2 with previous version 1.0-1 dated 2012-03-23

Title: A Laboratory for Recursive Partytioning
Description: A computational toolbox for recursive partitioning. The core of the package is ctree(), an implementation of conditional inference trees which embed tree-structured regression models into a well defined theory of conditional inference procedures. This non-parametric class of regression trees is applicable to all kinds of regression problems, including nominal, ordinal, numeric, censored as well as multivariate response variables and arbitrary measurement scales of the covariates. Based on conditional inference trees, cforest() provides an implementation of Breiman's random forests. The function mob() implements an algorithm for recursive partitioning based on parametric models (e.g. linear models, GLMs or survival regression) employing parameter instability tests for split selection. Extensible functionality for visualizing tree-structured regression models is available.
Author: Torsten Hothorn [aut, cre], Kurt Hornik [aut], Carolin Strobl [aut], Achim Zeileis [aut]
Maintainer: Torsten Hothorn

Diff between party versions 1.0-1 dated 2012-03-23 and 1.0-2 dated 2012-04-26

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Package glmmLasso updated to version 1.0.2 with previous version 1.0.1 dated 2012-03-29

Title: Variable selection for generalized linear mixed models by L1-penalized estimation
Description: Variable selection for generalized linear mixed models by L1-penalized estimation
Author: Andreas Groll
Maintainer: Andreas Groll

Diff between glmmLasso versions 1.0.1 dated 2012-03-29 and 1.0.2 dated 2012-04-26

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Package frmqa updated to version 0.1-1 with previous version 0.1-0 dated 2012-04-17

Title: Financial Risk Management and Quantitative Analysis
Description: R and C++ functions for financial risk management and quantative analysis, using the generalized perbolic and its related distributions.
Author: Thanh T. Tran
Maintainer: Thanh T. Tran

Diff between frmqa versions 0.1-0 dated 2012-04-17 and 0.1-1 dated 2012-04-26

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Package MASS updated to version 7.3-18 with previous version 7.3-17 dated 2012-02-08

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

Diff between MASS versions 7.3-17 dated 2012-02-08 and 7.3-18 dated 2012-04-26

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Package ivbma updated to version 1.02 with previous version 1.01 dated 2012-03-19

Title: Bayesian Instrumental Variable Estimation and Model Determination via Conditional Bayes Factors
Description: This package allows one incorporate instrument and covariate uncertainty into instrumental variable regression.
Author: Alex Lenkoski, Anna Karl, Andreas Neudecker
Maintainer: Alex Lenkoski

Diff between ivbma versions 1.01 dated 2012-03-19 and 1.02 dated 2012-04-26

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Package GLDEX updated to version 1.0.4.4 with previous version 1.0.4.3 dated 2012-03-08

Title: Fitting Single and Mixture of Generalised Lambda Distributions (RS and FMKL) using Various Methods
Description: The fitting algorithms considered in this package have two major objectives. One is to provide a smoothing device to fit distributions to data using the weight and unweighted discretised approach based on the bin width of the histogram. The other is to provide a definitive fit to the data set using the maximum likelihood and quantile matching estimation. Other methods such as moment matching, starship method, L moment matching are also provided. Diagnostics on goodness of fit can be done via qqplots, KS-resample tests and comparing mean, variance, skewness and kurtosis of the data with the fitted distribution.
Author: Steve Su, Diethelm Wuertz and Rmetrics core team members for low discrepancy algorithm, Robert King for gld C codes, Benjamin Dean for corrections and input in ks.gof code
Maintainer: Steve Su

Diff between GLDEX versions 1.0.4.3 dated 2012-03-08 and 1.0.4.4 dated 2012-04-26

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New package RfmriVC with initial version 1.0
Package: RfmriVC
Type: Package
Title: Varying stimulus coefficient fMRI models in R
Version: 1.0
Date: 2012-04-25
Author: Ludwig Bothmann, Stefanie Kalus
Maintainer: Stefanie Kalus
Description: A varying coefficient on the stimulus effect is introduced into the voxelwise fMRI regression model. By this the effects of the canonical hemodynamic response function are allowed to vary with another variable, like for example time or a vigilance parameter.
Depends: methods, splines, mvtnorm, mgcv, Rniftilib
License: GPL-2
Packaged: 2012-04-25 14:40:30 UTC; kalus
Repository: CRAN
Date/Publication: 2012-04-26 05:08:42

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Package DDD updated to version 1.1 with previous version 0.4 dated 2012-02-08

Title: Diversity-dependent diversification
Description: DDD implements maximum likelihood methods based on the diversity-dependent birth-death process to test whether speciation or extinction are diversity-dependent. See Etienne et al. 2012, Proc. Roy. Soc. B 279: 1300-1309, doi: 10.1098/rspb.2011.1439. DDD also implements a maximum likelihood method to detect key innovations defined as decoupling of diversity-dependence. See Etienne & Haegeman 2012, Am. Nat. In press.
Author: Rampal S. Etienne & Bart Haegeman
Maintainer: Rampal S. Etienne

Diff between DDD versions 0.4 dated 2012-02-08 and 1.1 dated 2012-04-26

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