EMPIRICAL BAYES ESTIMATION FOR FIRST-ORDER AUTOREGRESSIVE PROCESSES

DOI10.1111/j.1467-842X.1992.tb01048.xzbMath0751.62001OpenAlexW2000993426MaRDI QIDQ4014607

Young-Won Kim, Ishwar V. Basawa

Publication date: 12 October 1992

Published in: Australian Journal of Statistics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1111/j.1467-842x.1992.tb01048.x

zbMATH Keywords

maximum likelihood estimationfrequentistpanel dataempirical Bayes estimatefirst order autoregressive processlarge sample propertiesLarge sample properties

Mathematics Subject Classification ID

Asymptotic properties of parametric estimators (62F12) Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Empirical decision procedures; empirical Bayes procedures (62C12)

Related Items (11)

Parameter estimation in a stationary autoregressive process with correlated multiple observations ⋮ Large sample inference for a multivariate linear model with autocorrelated errors ⋮ Large sample estimation in nonstationary autoregressive processes with multiple observations ⋮ Maximum likelihood estimation for a fractionally differenced autoregressive model on a two-dimensional lattice ⋮ Random autoregressive models: A structured overview ⋮ The asymptotic distribution of the maximum likelihood estimator for a vector time series model with long memory dependence ⋮ Empirical Bayes prediction for a mixed linear model with autoregressive errors ⋮ Estimation in the multipath change point problem for correlated data ⋮ Limit Theory for Random Coefficient First-Order Autoregressive Process ⋮ Parameter estimation for generalized random coefficient autoregressive processes ⋮ Asymptotics for the random coefficient first-order autoregressive model with possibly heavy-tailed innovations

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