
TL;DR
This paper establishes necessary and sufficient conditions for additive functionals of Markov chains to admit martingale approximations, using operator theory and basis expansions to characterize when such decompositions are possible.
Contribution
It develops a comprehensive set of criteria for martingale approximation of Markov chain functionals, including operator-based conditions and basis expansion methods.
Findings
Provides necessary and sufficient conditions for martingale approximation.
Introduces a pseudo norm on $L^2(\pi)$ for analysis.
Identifies an orthonormal basis for $L_0^2(\pi)$ to facilitate criteria.
Abstract
Consider additive functionals of a Markov chain , with stationary (marginal) distribution and transition function denoted by and , say , where is square integrable and has mean 0 with respect to . If has the form , where is a square integrable martingale with stationary increments and , then is said to admit a martingale approximation. Necessary and sufficient conditions for such an approximation are developed. Two obvious necessary conditions are and . Assuming the first of these, let ; then defines a pseudo norm on the subspace of where it is finite. In one main result, a simple necessary and sufficient condition for a martingale approximation is developed…
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