Parameter estimation of an autoregressive moving average model

DOI10.1007/BF02481009zbMath0479.62068OpenAlexW2065252143MaRDI QIDQ1162091

Junji Nakano

Publication date: 1982

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

Full work available at URL: https://doi.org/10.1007/bf02481009

zbMATH Keywords

normalitymethod of least squaresNewton-Raphson methodasymptotically efficientlog smoothed periodogram

Mathematics Subject Classification ID

Asymptotic properties of parametric estimators (62F12) Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Monte Carlo methods (65C05) Probabilistic methods, stochastic differential equations (65C99)

Cites Work

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• Estimation for autoregressive moving average models in the time and frequency domains
• The Fitting of Time-Series Models
• Automatic Smoothing of the Log Periodogram
• The Estimation of the Prediction Error Variance
• The Inverse Autocorrelations of a Time Series and Their Applications
• Estimation of the Innovation Variance of a Stationary Time Series
• The estimation of mixed moving average autoregressive systems
• An exponential model for the spectrum of a scalar time series
• Large-sample estimation of parameters for autoregressive processes with moving-average residuals

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