Ergodicity of observation-driven time series models and consistency of the maximum likelihood estimator
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References listed on IDEAS
- Fokianos, Konstantinos & Rahbek, Anders & TjÃ¸stheim, Dag, 2009.
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CitationsCitations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
- Zheng, Tingguo & Xiao, Han & Chen, Rong, 2015. "Generalized ARMA models with martingale difference errors," Journal of Econometrics, Elsevier, vol. 189(2), pages 492-506.
- Lux, Thomas, 2017. "Estimation of agent-based models using sequential Monte Carlo methods," Economics Working Papers 2017-07, Christian-Albrechts-University of Kiel, Department of Economics.
- repec:eee:stapro:v:134:y:2018:i:c:p:15-21 is not listed on IDEAS
- Stella Kitromilidou & Konstantinos Fokianos, 2016. "Mallows’ quasi-likelihood estimation for log-linear Poisson autoregressions," Statistical Inference for Stochastic Processes, Springer, vol. 19(3), pages 337-361, October.
- Fukang Zhu & Lei Shi & Shuangzhe Liu, 2015. "Influence diagnostics in log-linear integer-valued GARCH models," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 99(3), pages 311-335, July.
- Ajay Jasra, 2015. "Approximate Bayesian Computation for a Class of Time Series Models," International Statistical Review, International Statistical Institute, vol. 83(3), pages 405-435, December.
More about this item
KeywordsConsistency; Ergodicity; Time series of counts; Maximum likelihood; Observation-driven models; Stationarity;
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