Markov models

Coupled Sampling Methods for Filtering

Fangyuan Yu, Ph.D. Student, Statistics

Mar 7, 15:00 - 17:00

KAUST

Monte carlo methods computational statistics Markov models

This thesis focuses on the use of multilevel Monte Carlo methods to achieve optimal error versus cost performance for statistical computations in hidden Markov models as well as for unbiased estimation under four cases: nonlinear filtering, unbiased filtering, unbiased estimation of hessian, continuous linear Gaussian filtering.

New paper accepted in Biometrics

1 min read · Tue, Aug 2 2022

COVID-19 Markov models Asymmetric Correlated binary data

New paper accepted: Zhang, Z., Arellano-Valle, R. B., Genton, M. G., and Huser, R. (2022+), Tractable Bayes of skew-elliptical link models for correlated binary data, Biometrics, to appear [ PDF preprint].