Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
5129860 | Statistics & Probability Letters | 2017 | 9 Pages |
Abstract
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
Related Topics
Physical Sciences and Engineering
Mathematics
Statistics and Probability
Authors
Yunwei Cui, Qi Zheng,