Estimation for a class of positive nonlinear time series models

DOI10.1016/0304-4149(96)00071-3zbMath0902.62101OpenAlexW2082078608MaRDI QIDQ1272160

Paul D. Feigin, Timothy C. Brown, Diana L. Pallant

Publication date: 23 November 1998

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

Full work available at URL: https://doi.org/10.1016/0304-4149(96)00071-3

zbMATH Keywords

weak convergenceMarkov chainsinfinitely divisible distributionmathematical programming estimator

Mathematics Subject Classification ID

Infinitely divisible distributions; stable distributions (60E07) Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Markov processes: estimation; hidden Markov models (62M05)

Related Items (2)

Asymptotic normality of the MLE in the level-effect ARCH model ⋮ Estimation for non-negative time series with heavy-tail innovations

Cites Work

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• Estimation for first-order autoregressive processes with positive or bounded innovations
• Markov chains and stochastic stability
• Weak convergence results for extremal processes generated by dependent random variables
• Limit distributions for linear programming time series estimators
• First-order autoregressive gamma sequences and point processes
• Estimation for autoregressive processes with positive innovations

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