Improved estimation for the autocovariances of a Gaussian stationary process

DOI10.1080/02331880701270515zbMath1120.62069OpenAlexW2032729908MaRDI QIDQ5423135

Hiroaki Ogata, Masanobu Taniguchi, Hiroshi Shiraishi

Publication date: 31 October 2007

Published in: Statistics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/02331880701270515

zbMATH Keywords

James-Stein estimatorshrinkage estimatorspectral densityautocovarianceempirical Bayes estimatormean squares error

Mathematics Subject Classification ID

Asymptotic properties of parametric estimators (62F12) Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Non-Markovian processes: estimation (62M09) Inference from stochastic processes and spectral analysis (62M15) Empirical decision procedures; empirical Bayes procedures (62C12)

Related Items (1)

Higher-order asymptotic theory of shrinkage estimation for general statistical models

Cites Work

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• Empirical Bayes estimation of the multivariate normal covariance matrix
• A central limit theorem for stationary processes and the parameter estimation of linear processes
• Asymptotic theory of statistical inference for time series
• Inadmissibility of the usual estimator for the variance of a normal distribution with unknown mean
• The Stein–James estimator for short- and long-memory Gaussian processes

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