Asymptotic Normality of the Posterior Distributions in a Class of Hidden Markov Models

Chunlei Wang; Sanvesh Srivastava

doi:10.48550/arXiv.2105.14394

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Asymptotic Normality of the Posterior Distributions in a Class of Hidden Markov Models

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Asymptotic Normality of the Posterior Distributions in a Class of Hidden Markov Models

Chunlei Wang and Sanvesh Srivastava

ArXiv.org

Cornell University

05/29/2021

DOI: 10.48550/arXiv.2105.14394

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Preprint (Author's original)This preprint has not been evaluated by subject experts through peer review. Preprints may undergo extensive changes and/or become peer-reviewed journal articles. Open Access

Abstract

We show that the posterior distribution of parameters in a hidden Markov model with parametric emission distributions and discrete and known state space is asymptotically normal. The main novelty of our proof is that it is based on a testing condition and the sequence of test functions is obtained using an optimal transportation inequality.

Details

Title: Subtitle: Asymptotic Normality of the Posterior Distributions in a Class of Hidden Markov Models
Creators: Chunlei Wang
Sanvesh Srivastava
Resource Type: Preprint
Publication Details: ArXiv.org
DOI: 10.48550/arXiv.2105.14394
ISSN: 2331-8422
Publisher: Cornell University
Language: English
Date posted: 05/29/2021
Academic Unit: Statistics and Actuarial Science
Record Identifier: 9984288740402771

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