9 citations · 41 across the 11 of their papers we have counts for
3 papers · 1 filter
High-dimensional structure learning of sparse vector autoregressive models using fractional marginal pseudo-likelihood
Kimmo Suotsalo, Yingying Xu, Jukka Corander +1
Learning vector autoregressive models from multivariate time series is conventionally approached through least squares or maximum likelihood estimation. These methods typically ass…
Generalised Bayes Updates with -divergences through Probabilistic Classifiers
Owen Thomas, Henri Pesonen, Jukka Corander
A stream of algorithmic advances has steadily increased the popularity of the Bayesian approach as an inference paradigm, both from the theoretical and applied perspective. Even wi…
Probabilistic elicitation of expert knowledge through assessment of computer simulations
Owen Thomas, Henri Pesonen, Jukka Corander
We present a new method for probabilistic elicitation of expert knowledge using binary responses of human experts assessing simulated data from a statistical model, where the param…