Functions to implement Generalized Direct Sampling


[Up] [Top]

Documentation for package ‘bayesGDS’ version 0.5.0

Help Pages

bayesGDS-package Functions to support implementation of the Braun and Damien (2011) Generalized Direct Sampling algorithm.
bayesGDS Functions to support implementation of the Braun and Damien (2011) Generalized Direct Sampling algorithm.
draw.MVN.proposals Draw from MVN, given mean and the Cholesky decomposition of the precision matrix
draw.thresholds Draw thresholds for the accept-reject stage of the GDS sampling algorithm.
get.GDS.draws Collect draws from the target posterior distribution.
get.LML Estimate log marginal likelihood of model
get.log.dens.MVN Evalaute a multivariate normal log density, given mean and the Cholesky decomposition of the precision matrix
inv.logit inverse logit function
inv.vech inverse vech operator on a vector
logit logit function
log_inv.logit log of inverse logit function
vech vech operator on a square matrix