High-order efficiency in the estimation of linear processes

DOI10.1214/AOS/1176344673zbMath0406.62067OpenAlexW2000372300MaRDI QIDQ1257751

Yuzo Hosoya

Publication date: 1979

Published in: The Annals of Statistics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1214/aos/1176344673

zbMATH Keywords

OptimalityMaximum Likelihood EstimateAsymptotic Information LossAymptotically Efficient EstimateCraig-Aitken TheoremGaussian Linear ProcessesInfinite- Dimensional Gaussian Random VectorsInformation AmountWhittle-Walker Model

Mathematics Subject Classification ID

Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Gaussian processes (60G15) Statistical aspects of information-theoretic topics (62B10)

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On Bahadur asymptotic efficiency of the maximum likelihood and quasi-maximum likelihood estimators in Gaussian stationary processes ⋮ Information amount and higher-order efficiency in estimation ⋮ Second-order properties of locally stationary processes ⋮ More higher-order efficiency: Concentration probability

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