The MCMC split sampler: A block Gibbs sampling scheme for latent Gaussian models

Understand

A novel computationally efficient Markov chain Monte Carlo (MCMC) scheme for latent Gaussian models (LGMs) is proposed in this paper.

• The sampling scheme is a two block Gibbs sampling scheme designed to exploit the model structure of LGMs.
• We refer to the proposed sampling scheme as the MCMC split sampler.
• The principle idea behind the MCMC split sampler is to split the latent Gaussian parameters into two vectors.