MTD models for aggregate data from higher order Markov chains

We consider two higher order models for aggregate data on a finite state space. In the first model, aggregate data are obtained from N i.i.d. individuals who follow Mixture Transition Distribution (MTD) Markov model of lag l. In the second model, aggregate data are modeled as a MTD Markov model based on multinomial thinning. In both the cases, it is shown that Conditional Least Square Estimators are CAN for a fixed N.

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Year of publication:	2014
Authors:	Kaur, Inderdeep
Published in:	Statistics & Probability Letters. - Elsevier, ISSN 0167-7152. - Vol. 88.2014, C, p. 157-164
Publisher:	Elsevier
Subject:	Aggregate data \| MTD model \| Conditional Least Squares \| Markov chains \| Multinomial thinning

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

Persistent link: https://www.econbiz.de/10010752964