Comments for Umberto Picchini's research blog
https://umbertopicchini.wordpress.com
Statistical inference for stochastic modelling, likelihood-free methods for intractable likelihoods, Bayes and computational statisticsWed, 28 Mar 2018 15:39:41 +0000hourly1http://wordpress.com/Comment on Why and how pseudo-marginal MCMC work for exact Bayesian inference by State space models and intractable likelihoods | Umberto Picchini's research blog
https://umbertopicchini.wordpress.com/2018/03/26/why-and-how-pseudo-marginal-mcmc-work-for-exact-bayesian-inference/comment-page-1/#comment-56
Wed, 28 Mar 2018 15:39:41 +0000http://umbertopicchini.wordpress.com/?p=2191#comment-56[…] framework. In a series of 4-5 posts I will construct the simplest example of this class of pseudo-marginal algorithms, now considered the state-of-art tool for parameter estimation in nonlinear state space […]

]]>Comment on State space models and intractable likelihoods by Why and how pseudo-marginal MCMC work for exact Bayesian inference | Umberto Picchini's research blog
https://umbertopicchini.wordpress.com/2016/10/10/state-space-models-intractable-likelihoods/comment-page-1/#comment-55
Mon, 26 Mar 2018 15:23:29 +0000http://umbertopicchini.wordpress.com/?p=15#comment-55[…] we use Metropolis-Hastings in a Bayesian context to simulate from a specific distribution, the posterior distribution for a parameter , given data . From Bayes’ theorem we have , with the prior of , the […]

]]>Comment on Monte Carlo sampling for likelihood approximation in state space models by Why and how pseudo-marginal MCMC work for exact Bayesian inference | Umberto Picchini's research blog
https://umbertopicchini.wordpress.com/2016/10/13/monte-carlo-sampling-likelihood-approximation-state-space-models/comment-page-1/#comment-54
Mon, 26 Mar 2018 15:23:27 +0000http://umbertopicchini.wordpress.com/?p=556#comment-54[…] the above assumes that we are able to evaluate at every (this construction naturally applies to state-space models, when we consider as “data” and the as […]

]]>Comment on Tips for coding a Metropolis-Hastings sampler by Why and how pseudo-marginal MCMC work for exact Bayesian inference | Umberto Picchini's research blog
https://umbertopicchini.wordpress.com/2017/12/18/tips-for-coding-a-metropolis-hastings-sampler/comment-page-1/#comment-53
Mon, 26 Mar 2018 15:23:25 +0000http://umbertopicchini.wordpress.com/?p=2467#comment-53[…] ← Tips for coding a Metropolis-Hastings sampler […]

]]>Comment on State space models and intractable likelihoods by Sequential Monte Carlo and the bootstrap filter | Umberto Picchini's research blog
https://umbertopicchini.wordpress.com/2016/10/10/state-space-models-intractable-likelihoods/comment-page-1/#comment-5
Wed, 19 Oct 2016 09:26:22 +0000http://umbertopicchini.wordpress.com/?p=15#comment-5[…] could be plugged into a Bayesian procedure for sampling from the posterior distribution (more on this in future […]

]]>Comment on Monte Carlo sampling for likelihood approximation in state space models by Sequential Monte Carlo and the bootstrap filter | Umberto Picchini's research blog
https://umbertopicchini.wordpress.com/2016/10/13/monte-carlo-sampling-likelihood-approximation-state-space-models/comment-page-1/#comment-4
Wed, 19 Oct 2016 09:26:19 +0000http://umbertopicchini.wordpress.com/?p=556#comment-4[…] ← Monte Carlo sampling for likelihood approximation in state space models […]