Forgetting of the initial distribution for Hidden Markov Models
| dc.creator | Douc, Randal | |
| dc.creator | Fort, Gersende | |
| dc.creator | Moulines, Eric | |
| dc.creator | Priouret, Pierre | |
| dc.date | 2007-03-28 | |
| dc.date.accessioned | 2026-07-07T09:51:05Z | |
| dc.date.available | 2026-07-07T09:51:05Z | |
| dc.description | The forgetting of the initial distribution for discrete Hidden Markov Models (HMM) is addressed: a new set of conditions is proposed, to establish the forgetting property of the filter, at a polynomial and geometric rate. Both a pathwise-type convergence of the total variation distance of the filter started from two different initial distributions, and a convergence in expectation are considered. The results are illustrated using different HMM of interest: the dynamic tobit model, the non-linear state space model and the stochastic volatility model. | |
| dc.identifier | https://arxiv.org/abs/math/0703836 | |
| dc.identifier | http://arxiv.org/abs/math/0703836 | |
| dc.identifier | Stochastic Processes and their Applications (2008) A paraitre | |
| dc.identifier.uri | http://salesiana.dossiersoluciones.com/handle/123456789/165166 | |
| dc.subject | Statistics Theory | |
| dc.subject | ACM : 93E11, 60B10,60G35 | |
| dc.title | Forgetting of the initial distribution for Hidden Markov Models | |
| dc.type | text |