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Optimal direction Gibbs sampler for truncated multivariate normal distributions
Communications in statistics. Simulation and computation
Generalized Gibbs samplers simulate from any direction, not necessarily limited to the coordinate directions of the parameters of the objective function. We study how to optimally choose such directions in a random scan Gibbs sampler setting. We consider that optimal directions will be those that minimize the Kullback-Leibler divergence of two Markov chain Monte Carlo steps. Two distributions over direction are proposed for the multivariate Normal objective function. The resulting algorithmsdoi:10.1080/03610918.2015.1053926 fatcat:kjqd4xdk6fhevbpkkfqne6zcny