_:n299b451a1b6c48cf87e27db12d75df1fxb44
<http://schema.org/description>
"The integrated nested Laplace approximation (INLA) for Bayesian inference is\nan efficient approach to estimate the posterior marginal distributions of the\nparameters and latent effects of Bayesian hierarchical models that can be\nexpressed as latent Gaussian Markov random fields (GMRF). The representation as\na GMRF allows the associated software R-INLA to estimate the posterior\nmarginals in a fraction of the time as typical Markov chain Monte Carlo\nalgorithms. INLA can be extended by means of Bayesian model averaging (BMA) to\nincrease the number of models that it can fit to conditional latent GMRF. In\nthis paper we review the use of BMA with INLA and propose a new example on\nspatial econometrics models."
<https://api.deepai.org/profile/virgilio-gomez-rubio>