A new threshold INAR(1) model based on modified negative binomial operator with random coefficient

Abstract

In this paper, a new threshold INAR(1) model based on modified negative binomial operator with random coefficient is proposed. Basic probabilistic and statistical properties of this process are established. Then the conditional least squares (CLS) and the conditional maximum likelihood (CML) methods are applied to estimate the model parameters when the threshold value is known or not. The asymptotic properties of the CLS-estimator and the CML-estimator are also been discussed. A method to test the constancy of the autoregressive parameters is provided. As an illustration, a simulation study is conducted to illustrate the performances of these estimators and present an empirical analysis of monthly counts of break and enter non-dwelling in Bellingen.

Keywords:

• Threshold integer-valued time series models
• INAR
• threshold autoregressive model
• negative binomial operatornn
• random coefficient models

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

This work is supported by the National Natural Science Foundation of China [grant numbers 12271231, 11871028, 11731015, 11901053] and China Scholarship Council [grant number CSC202206170056].