2015•Theory of Probability and Its ApplicationsRequires access

Asymptotic Normality of Local Averaging Estimates for Weakly Dependent Random Fields

A. P. Shashkin

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Abstract

We consider a family of estimates of asymptotic variance of a stationary random field endowed with weak dependence property more general than positive or negative association. For such estimates with local averaging the asymptotic normality is proved, allowing to construct asymptotic confidence intervals for unknown variance under some additional conditions. A functional central limit theorem is also established.

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We consider a family of estimates of asymptotic variance of a stationary random field endowed with weak dependence property more general than positive or negative association. For such estimates with local averaging the asymptotic normality is proved, allowing to construct asymptotic confidence intervals for unknown variance under some additional conditions. A functional central limit theorem is also established.

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Available abstract

We consider a family of estimates of asymptotic variance of a stationary random field endowed with weak dependence property more general than positive or negative association. For such estimates with local averaging the asymptotic normality is proved, allowing to construct asymptotic confidence intervals for unknown variance under some additional conditions. A functional central limit theorem is also established.

Key concepts: Mathematics, Asymptotic distribution, Local asymptotic normality, Central limit theorem, Delta method, Limit (mathematics), Normality, Random field

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