[Forum SIS] Seminar Geir Drage Berentsen

[Marco Alfo']

Apologies for cross-posting


---- SEMINAR (PhD School in Statistical Sciences) ----
Tuesday 8 may 20178, 11.00-12.00 room 34,
IVth floor, Statistical Sciences building, Sapienza Universita' di Roma

Speaker: Geir Drage Berentsen, University of Bergen

*Pros and cons of Laplace approximations in mixed hidden Markov models*

Abstract: Hidden Markov models (HMMs) are a popular tool for modelling
temporal data and has been successfully applied to many problems. Using
HMMs for analysing multiple processes, such as longitudinal data, have not
yet gained the same popularity. This is partly due to the computational
complexity involved in adjusting for heterogeneity in the data, which
typically involves numerical or Monte Carlo approximations of multiple
integrals. Implications of different model formulations for mixed Hidden
Markov models (mHMMs) and pros and cons of using Laplace approximations to
obtain the likelihood of the data are discussed. Applications of the method
to both real and simulated data will be presented.
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