@article {10.3844/jmssp.2019.250.258, article_type = {journal}, title = {Poisson Quasi-Maximum Likelihood Estimator-based CUSUM Test for Integer-Valued Time Series}, author = {Lee, Sangyeol}, volume = {15}, year = {2019}, month = {Oct}, pages = {250-258}, doi = {10.3844/jmssp.2019.250.258}, url = {https://thescipub.com/abstract/jmssp.2019.250.258}, abstract = {This study considers the parameter change test for integer-valued time series models based on the Poisson quasi-maximum likelihood estimates. As a change point test, we consider the score vector-based CUSUM test and show that its limiting null distribution takes the form of a function of Brownian bridges. Moreover, the residual-based CUSUM tests are considered as alternatives. For evaluation, we conduct a Monte Carlo simulation study with Poisson, zero-inflated Poisson, negative binomial and Conway-Maxwell integer-valued generalized autoregressive conditional heteroscedastic models andPoisson integer-valued autoregressive models, and compare the performance of the proposed CUSUM tests. Our findings confirm that the proposed test is a functional tool for detecting a change point when the underlying distribution is unspecified.}, journal = {Journal of Mathematics and Statistics}, publisher = {Science Publications} }