Inference in Hidden Markov Models

Bibliographic ressources

• Reference (Cappé, O. - 2001b) is online here: [html|pdf]
• The BibTeX file for the book
• Recent publications on the topics of the book by the autors include
  • R. Douc, E. Moulines, Y. Ritov. Forgetting of the initial condition for the filter in general state-space hidden Markov chain: a coupling approach.
  • R. Douc, E. Moulines, J. Olsson. On the auxiliary particle filter.
  • J. Olsson, O. Cappé, R. Douc, and E. Moulines. Sequential Monte Carlo smoothing with application to parameter estimation in non-linear state space models. Technical report, Lund University, 2006.
  • R. Douc, O. Cappé, and E. Moulines. Comparison of Resampling Schemes for Particle Filtering. In 4th International Symposium on Image and Signal Processing and Analysis (ISPA), Zagreb, Croatia, September 2005.
  • J. Olsson, T. Rydén. Asymptotic properties of the bootstrap particle filter maximum likelihood estimator for state space models. Technical report, Lund University, n. 2005:18.
  • R. Douc., E. Moulines. Limit theorems for weighted samples with applications to Sequential Monte Carlo Methods. Technical report 2005.