Quotation Hahn, Markus, Frühwirth-Schnatter, Sylvia, Sass, Jörn. 2009. Estimating models based on Markov jump processes given fragmented observation series. Advances in Statistical Analysis 93 403-425.




We consider the problem of estimating the rate matrix governing a finitestate Markov jump process given a number of fragmented time series. We propose to concatenate the observed series and to employ the emerging non-Markov process for estimation.We describe the bias arising if standard methods forMarkov processes are used for the concatenated process, and provide a post-processing method to correct for this bias. This method applies to discrete-timeMarkov chains and to more general models based on Markov jump processes where the underlying state process is not observed directly. This is demonstrated in detail for a Markov switching model. We provide applications to simulated time series and to financial market data, where estimators resulting from maximum likelihood methods and Markov chain Monte Carlo sampling are improved using the presented correction.


Press 'enter' for creating the tag

Publication's profile

Status of publication Published
Affiliation WU
Type of publication Journal article
Journal Advances in Statistical Analysis (AStA)
Citation Index SCI
WU-Journal-Rating new FIN-A, VW-D
Language English
Title Estimating models based on Markov jump processes given fragmented observation series
Volume 93
Year 2009
Page from 403
Page to 425
URL http://www.springerlink.com/content/r6581113431j1237/fulltext.pdf


Frühwirth-Schnatter, Sylvia (Details)
Hahn, Markus
Sass, Jörn
Institute for Statistics and Mathematics IN (Details)
Google Scholar: Search