MTD models for aggregate data from higher order Markov chains

Inderdeep Kaur

Statistics & Probability Letters, 2014, vol. 88, issue C, 157-164

Abstract: 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.

Keywords: Aggregate data; MTD model; Conditional Least Squares; Markov chains; Multinomial thinning (search for similar items in EconPapers)
Date: 2014
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DOI: 10.1016/j.spl.2014.02.002

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