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Title: On Bayesian estimation for the linear ballistic accumulator model Authors:  Robert Kohn - University of New South Wales (Australia) [presenting]
David Gunawan - University of Wollongong (Australia)
Thanh Mai Pham Ngoc - University Paris Sud Orsay (France)
Scott Brown - University of Newcastle (Australia)
Abstract: The aim is to estimate a hierarchical version of the Linear Ballistic Accumulator (LBA) model. In general, estimating such models is challenging because the likelihood is an integral over the latent individual random effects and the observations are not Gaussian. Two Bayesian approaches are proposed in order to estimate the hierarchical version of the LBA model. Both methods are based on recent advances in particle Markov chain Monte Carlo (PMCMC)methods. The first approach is an extended version of PMCMC sampler of and the second is based on annealing importance sampling for intractable likelihood (AISIL) method. An estimate of the marginal likelihood is obtained as a by product of the AISIL method. We apply the proposed methods to simulated and real datasets.