Normality test in random coefficient autoregressive models

In this paper, we consider the problem of testing for normality of the two unobservable random processes included in the first order random coefficient autoregressive models. To this end, we propose an information matrix based test and derive its limiting null distribution. We conduct simulations to evaluate the performance and characteristics of the introduced test, and provide a real data analysis.

Automated summary

This paper considers the problem of testing for normality of the two unobservable random processes in first order random coefficient autoregressive models. An information matrix based test is proposed and its limiting null distribution is derived. Simulations are conducted to evaluate the performance and characteristics of the introduced test, and a real data analysis is provided.