• Dr. Maitreya N. Acharya

In this research paper, we shall apply the concept of change point inference problem. For that let us consider first order autoregressive process with changing autoregressive coefficient at some point of time, say ‘m’. This is called change point inference problem. Here, we have used RWM-H (Random Walk Metropolis - Hasting) Algorithm and Gibbs Sampling Technique for the Bayes Estimation of ‘m’ and autoregressive coefficient. Further, we have studied the effects of prior information on the Bayes Estimates obtained.

First Order Auto Regressive AR (1) Process, AR (1) Model, Autoregressive Coefficient, RWM-H Algorithm, Gibbs Sampling Technique, Bayes Estimates, Change Point

"A STUDY ON FIRST ORDER AUTOREGRESSIVE PROCESS AR (1) WITH CHANGING AUTOREGRESSIVE COEFFICIENT AND A CHANGE POINT MODEL FROM BAYESIAN PERSPECTIVE", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.8, Issue 12, page no.a186-a195, December-2021, Available :http://www.jetir.org/papers/JETIR2112023.pdf

"A STUDY ON FIRST ORDER AUTOREGRESSIVE PROCESS AR (1) WITH CHANGING AUTOREGRESSIVE COEFFICIENT AND A CHANGE POINT MODEL FROM BAYESIAN PERSPECTIVE", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.8, Issue 12, page no. ppa186-a195, December-2021, Available at : http://www.jetir.org/papers/JETIR2112023.pdf