General-order observation-driven models: ergodicity and consistency of the maximum likelihood estimator

DOI10.1214/21-EJS1858zbMath1472.62136arXiv2106.05201OpenAlexW3175353329MaRDI QIDQ2044417

Randal Douc, Tepmony Sim, François Roueff

Publication date: 9 August 2021

Published in: Electronic Journal of Statistics (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/2106.05201

zbMATH Keywords

consistencyergodicitymaximum likelihoodtime series of countsobservation-driven modelsgeneral-order

Mathematics Subject Classification ID

Asymptotic properties of parametric estimators (62F12) Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Point estimation (62F10) Markov processes: estimation; hidden Markov models (62M05)

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