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Normal Approximation for Functions of Hidden Markov Models
Published online by Cambridge University Press: 06 June 2022
Abstract
The generalized perturbative approach is an all-purpose variant of Stein’s method used to obtain rates of normal approximation. Originally developed for functions of independent random variables, this method is here extended to functions of the realization of a hidden Markov model. In this dependent setting, rates of convergence are provided in some applications, leading, in each instance, to an extra log-factor vis-à-vis the rate in the independent case.
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- © The Author(s), 2022. Published by Cambridge University Press on behalf of Applied Probability Trust
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