On selection of the order of the spectral density model for a stationary process

DOI10.1007/BF02480345zbMath0455.62073OpenAlexW1985277119MaRDI QIDQ1150228

Masanobu Taniguchi

Publication date: 1980

Published in: Annals of the Institute of Statistical Mathematics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/bf02480345

zbMATH Keywords

predictionAkaike information criterionspectral densitybest linear predictor

Mathematics Subject Classification ID

Inference from stochastic processes and prediction (62M20) Non-Markovian processes: estimation (62M09) Stationary stochastic processes (60G10) Inference from stochastic processes and spectral analysis (62M15)

Related Items (6)

On a criterion for the selection of models for stationary time series ⋮ On Efficient AR Spectral Estimation for Long-Range Predictions ⋮ ON THE UNBIASEDNESS PROPERTY OF AIC FOR EXACT OR APPROXIMATING LINEAR STOCHASTIC TIME SERIES MODELS ⋮ Generalized Levinson--Durbin and Burg algorithms. ⋮ Local asymptotic admissibility of a generalization of Akaike's model selection rule ⋮ ON SOME AMBIGUITIES ASSOCIATED WITH THE FITTING OF ARMA MODELS TO TIME SERIES

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• Asymptotic properties of least-squares estimates of parameters of the spectrum of a stationary non-deterministic time-series
• A new look at the statistical model identification

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