A fixed point characterization for bias of autoregressive estimators

DOI10.1214/aos/1176347268zbMath0681.62075OpenAlexW1984240965MaRDI QIDQ1823595

Robert A. Stine, Paul Shaman

Publication date: 1989

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

Full work available at URL: https://doi.org/10.1214/aos/1176347268

zbMATH Keywords

contractiontime seriesautocorrelation functionbiasspectral densityLeast squares estimatorsunknown meanknown meanboot-strapping autoregressive modelsdifferent orders of autoregressionDurbin-Levinson recursionfixed point modelsleast squares approximations to an infinite- order autoregressionYule- Walker estimators

Mathematics Subject Classification ID

Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10)

Related Items (7)

Polarization of forecast densities: a new approach to time series classification ⋮ A hypothesis test using bias-adjusted AR estimators for classifying time series in small samples ⋮ Bias-correction and endogenous lag order algorithm for bootstrap prediction intervals. Discussion on: ``Bootstrap prediction intervals for linear, nonlinear and nonparametric autoregressions ⋮ Improving the finite sample performance of tests for a shift in mean ⋮ Generalized Levinson-Durbin sequences, binomial coefficients and autoregressive estimation ⋮ Bias Reduction through First-order Mean Correction, Bootstrapping and Recursive Mean Adjustment ⋮ Bias reduction in autoregressive models

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