Estimation for first-order autoregressive processes with positive or bounded innovations

DOI10.1016/0304-4149(89)90090-2zbMath0692.62070OpenAlexW2079369736MaRDI QIDQ583792

William P. McCormick, Richard A. Davis

Publication date: 1989

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

Full work available at URL: https://doi.org/10.1016/0304-4149(89)90090-2

zbMATH Keywords

exponential distributionuniform distributionextreme value theoryleast squares estimatormaximum likelihood estimatorslimit distributioncorrelation parameterexponent of regular variationfirst order autoregression processinnovation distributionpoint process methods

Mathematics Subject Classification ID

Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Asymptotic distribution theory in statistics (62E20) Central limit and other weak theorems (60F05) Non-Markovian processes: estimation (62M09)

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Cites Work

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• Extremes of moving averages of random variables from the domain of attraction of the double exponential distribution
• Weak convergence results for extremal processes generated by dependent random variables
• Asymptotic behavior of least-squares estimates for autoregressive processes with infinite variances
• Maximum likelihood estimation of translation parameter of truncated distribution. II
• Maximum likelihood estimation in a class of nonregular cases
• An exponential moving-average sequence and point process (EMA1)
• First-order autoregressive gamma sequences and point processes
• Dams with autoregressive inputs

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