Description: Provides a way to simulate from the prior distribution of Bayesian trees by Chipman et al. (1998) <DOI:10.2307/2669832>. The prior distribution of Bayesian trees is highly dependent on the design matrix X, therefore using the suggested hyperparameters by Chipman et al. (1998) <DOI:10.2307/2669832> is not recommended and could lead to unexpected prior distribution. This work is part of my master thesis (In revision, expected 2016) and a journal publication I'm working on.

Title: Bayesian Analysis of Item-Level Twin Data
Depends: R (>= 3.4.0), foreign, coda, matrixStats, rjags
Description: Bayesian analysis of item-level hierarchical twin data using an integrated item response theory model. Analyses are based on Schwabe & van den Berg (2014) <doi:10.1007/s10519-014-9649-7>, Molenaar & Dolan (2014) <doi:10.1007/s10519-014-9647-9>, Schwabe, Jonker & van den Berg (2016) <doi:10.1007/s10519-015-9768-9> and Schwabe, Boomsma & van den Berg (2016) <doi:10.1016/j.lindif.2017.01.018>.

Description: BayesValidate implements the software validation method
described in the paper "Validation of Software for Bayesian
Models using Posterior Quantiles" (Cook, Gelman, and Rubin,
2005).  It inputs a function to perform Bayesian inference as
well as functions to generate data from the Bayesian model
being fit, and repeatedly generates and analyzes data to check
that the Bayesian inference program works properly.
Packaged: Thu Mar 30 10:48:35 2006; hornik

Package: BayesVarSel
Type: Package
Title: Bayesian Variable selection in Linear Models
Version: 1.0
Date: 2012-11-20
Author: Gonzalo Garcia-Donato and Anabel Forte
Maintainer: Anabel Forte <forte@uji.es>
Description: Within the context of the lineal model, this package
provides tools for the analysis of the variable selection
problem from a Bayesian perspective. Special emphasis is placed
on providing simple and intuitive methods to explore and
synthesize the results. BayesVarSel allows the calculations to
be performed either exactly (sequential or paralel computation)
or heuristically, using a Gibbs sampling algorithm studied in
Garcia-Donato and Martinez-Beneito (2012). The default
implementation takes advantage of a closed-form expression for
the posterior probabilities that the prior proposed in Bayarri,
Berger, Forte and Garcia-Donato (2012) produces. Nevertheless,
other alternative priors, like Zellner (1986) g-prior,
Zellner-Siow (1980,1984) or Liang, Paulo, Molina, Clyde and
Berger (2008) can be used.
Depends: R (>= 2.15.0), snow, MASS
License: GPL-2
Packaged: 2012-12-12 17:12:27 UTC; Anabel
Repository: CRAN
Date/Publication: 2012-12-12 20:30:10