  Change point analysis has become an important research topic in many fields
of applications. Several research work has been carried out to detect changes
and its locations in time series data. In this paper, a nonparametric method
based on the empirical likelihood is proposed to detect the structural changes
of the parameters in autoregressive (AR) models . Under certain conditions, the
asymptotic null distribution of the empirical likelihood ratio test statistic
is proved to be the extreme value distribution. Further, the consistency of the
test statistic has been proved. Simulations have been carried out to show that
the power of the proposed test statistic is significant. The proposed method is
applied to real world data set to further illustrate the testing procedure.
