Cluster priors in the Bayesian modelling of fMRI data
PublisherUniversity of Jyväskylä
MetadataShow full item record
- Väitöskirjat 
Showing items with similar title or keywords.
Vihola, Matti; Helske, Jouni; Franks, Jordan (Wiley-Blackwell, 2020)We consider importance sampling (IS) type weighted estimators based on Markov chain Monte Carlo (MCMC) targeting an approximate marginal of the target distribution. In the context of Bayesian latent variable models, the ...
Karppinen, Santeri; Vihola, Matti (Springer, 2021)Conditional particle filters (CPFs) are powerful smoothing algorithms for general nonlinear/non-Gaussian hidden Markov models. However, CPFs can be inefficient or difficult to apply with diffuse initial distributions, which ...
Helske, Satu (University of Jyväskylä, 2016)
On the use of approximate Bayesian computation Markov chain Monte Carlo with inflated tolerance and post-correction Vihola, Matti; Franks, Jordan (Oxford University Press, 2020)Approximate Bayesian computation enables inference for complicated probabilistic models with intractable likelihoods using model simulations. The Markov chain Monte Carlo implementation of approximate Bayesian computation ...
Kuronen, Mikko; Särkkä, Aila; Vihola, Matti; Myllymäki, Mari (Springer Science and Business Media LLC, 2021)We propose a hierarchical log Gaussian Cox process (LGCP) for point patterns, where a set of points xx affects another set of points yy but not vice versa. We use the model to investigate the effect of large trees on the ...