Tag Archives: Bayesian inference
Why and how pseudo-marginal MCMC work for exact Bayesian inference
I will describe a breakthrough strategy for “exact-approximate” Bayesian inference. The apparent contradiction in the terminology is due to the surprising result in Beaumont (2003) and Andrieu and Roberts (2009) where it is shown that plugging a non-negative and unbiased … Continue reading
Monte Carlo sampling for likelihood approximation in state space models
In a previous post I have set the problem of estimating parameters for a state-space model (SSM). That post is a required read, also because I set some notation. My final goal is to show how to construct exact Bayesian … Continue reading
State space models and intractable likelihoods
In this first series of posts, I introduce important tools to construct inference methods for the estimation of parameters in stochastic models. Stochastic models are characterized by randomness in their mathematical nature, and since at first I focus on models … Continue reading
Umberto Picchini's research blog 