Observation-driven generalized state space models for categorical time series

Observation-driven state space models are presented for categorical time series as an alternative to the regression type models which are commonly used in the literature. As an application to multi-categorical time series, we present a DNA data analysis and demonstrate the advantages of using state space models.

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Year of publication:	2009
Authors:	Zhen, X. ; Basawa, I.V.
Published in:	Statistics & Probability Letters. - Elsevier, ISSN 0167-7152. - Vol. 79.2009, 24, p. 2462-2468
Publisher:	Elsevier

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Type of publication:	Article
Source:	RePEc - Research Papers in Economics

Persistent link: https://www.econbiz.de/10008474328