A note on asymptotic inference in a class of non-stationary processes

DOI10.1016/0304-4149(83)90055-8zbMath0522.62069OpenAlexW1982793583MaRDI QIDQ1056179

Anders Rygh Swensen

Publication date: 1983

Published in: Stochastic Processes and their Applications (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/0304-4149(83)90055-8

zbMATH Keywords

non-stationary processesasymptotic decision theorycriterion for efficiency of tests based upon existence of uniformly most powerful testslocally asymptotically mixed normalsupercritical Galton-Watson branching processes

Mathematics Subject Classification ID

Bayesian inference (62F15) Statistical decision theory (62C99) Non-Markovian processes: hypothesis testing (62M07) Asymptotic properties of parametric tests (62F05)

Related Items (4)

Asymptotic theory of conditional inference for stochastic processes ⋮ Minimaxity of Pitman estimators ⋮ A note on statistical inference for a class of diffusions and approximate diffusions ⋮ Unit root tests for cross-sectionally dependent panels: the influence of observed factors

Cites Work

• Asymptotic tests of composite hypotheses for non-ergodic type stochastic processes
• Asymptotic inference for stochastic processes
• Uniform asymptotic normality of the maximum likelihood estimator
• The efficiency criteria problem for stochastic processes
• On an optimal asymptotic property of the maximum likelihood estimator of a parameter from a stochastic process
• Efficient tests for branching processes
• On efficient tests for branching processes
• A characterization of limiting distributions of regular estimates
• On the Assumptions Used to Prove Asymptotic Normality of Maximum Likelihood Estimates
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