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.
| 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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