Conditional maximum likelihood estimation for a class of observation-driven time series models for count data
Yunwei Cui and
Statistics & Probability Letters, 2017, vol. 123, issue C, 193-201
This paper investigates the statistical inference for a class of observation-driven time series models of count data based on the conditional maximum likelihood estimator (CMLE), where the conditional distribution of the observed count given a state process is from the one-parameter exponential family. Under certain regularity conditions, the strong consistency and asymptotic normality of the CMLE of the misspecified likelihood function are established.
Keywords: Observation-driven models; One-parameter exponential family; INGARCH(p,q) models; Time series of counts (search for similar items in EconPapers)
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Persistent link: https://EconPapers.repec.org/RePEc:eee:stapro:v:123:y:2017:i:c:p:193-201
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