Empirical Likelihood Inference for First-Order Random Coefficient Integer-Valued Autoregressive Processes

Abstract

We apply the empirical likelihood method to estimate the variance of random coefficient in the first-order random coefficient integer-valued autoregressive (RCINAR(1)) processes. The empirical likelihood ratio statistic is derived and some asymptotic theory for it is presented. Furthermore, a simulation study is presented to demonstrate the performance of the proposed method.

Interval Estimation of Random Coefficient Integer-Valued Autoregressive Model Based on Mean Empirical Likelihood Method

“…e EL method is a useful tool for statistical inference and has been successfully applied to many areas, such as linear regression models [22], generalized linear models [23], generalized estimation equations [24], dependent processes [25], semiparametric varying-coefficient partially linear regression models [26], and the limit theory of RCINAR(1) processes [27]. Zhao and Yu [28] estimated the variance of the random coefficient in the RCINAR(1) process by the EL method.…”