On the preservation of local asymptotic normality under information loss

DOI10.1214/aos/1176350817zbMath0661.62016OpenAlexW2052672416WikidataQ101584176 ScholiaQ101584176MaRDI QIDQ1113230

Grace L. Yang, Lucien Le Cam

Publication date: 1988

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

Full work available at URL: https://doi.org/10.1214/aos/1176350817

zbMATH Keywords

asymptotic normalityinformation lossLAN conditionsnegligibility conditionsone step estimatesunobservable random variables

Mathematics Subject Classification ID

Asymptotic properties of parametric estimators (62F12) Asymptotic properties of nonparametric inference (62G20) Markov processes: estimation; hidden Markov models (62M05) Asymptotic properties of parametric tests (62F05)

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Laslett's line segment problem ⋮ Frequentist validity of Bayesian limits ⋮ One-step robust parametric estimation with application to random censoring model ⋮ Asymptotic normality of maximum likelihood and its variational approximation for stochastic blockmodels ⋮ Local consistency of Markov chain Monte Carlo methods ⋮ Information bounds for Gaussian copulas ⋮ Filtered likelihood for point processes ⋮ Estimation of open dwell time and problems of identifiability in channel experiments ⋮ Efficient robust estimation of parameter in the random censorship model ⋮ Asymptotic linearity of minimax estimators ⋮ Root- estimability of some missing data models ⋮ ASYMPTOTICALLY UMP PANEL UNIT ROOT TESTS—THE EFFECT OF HETEROGENEITY IN THE ALTERNATIVES ⋮ Combined sample scores versus two-sample scores under censoring

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