EconPapers    
Economics at your fingertips  
 

Computing the observed information in the hidden Markov model using the EM algorithm

James P. Hughes

Statistics & Probability Letters, 1997, vol. 32, issue 1, 107-114

Abstract: A method of computing the observed information for the hidden Markov model using the EM algorithm and the results of Louis (1982) is described. Generating the "exact" information may be computationally intensive for large datasets but an approximation is given which significantly reduces the computational effort in most cases.

Keywords: Hidden; Markov; model; EM; algorithm; Information (search for similar items in EconPapers)
Date: 1997
References: View complete reference list from CitEc
Citations:

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0167-7152(96)00062-4
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:stapro:v:32:y:1997:i:1:p:107-114

Ordering information: This journal article can be ordered from
http://www.elsevier.com/wps/find/supportfaq.cws_home/regional
https://shop.elsevie ... _01_ooc_1&version=01

Access Statistics for this article

Statistics & Probability Letters is currently edited by Somnath Datta and Hira L. Koul

More articles in Statistics & Probability Letters from Elsevier
Bibliographic data for series maintained by Catherine Liu ().

 
Page updated 2025-03-19
Handle: RePEc:eee:stapro:v:32:y:1997:i:1:p:107-114