New family of time series models and its bayesian analysis

A new family of time series models, called the Full Range Autoregressive model, is introduced which avoids the difficult problem of order determination in time series analysis. Some of the basic statistical properties of the new model are studied. Further, the paper describes the Bayesian inference and forecasting as applied to the Full Range Autoregressive model. The Canadian lynx data is used to compare the efficiency of the predictive power of the new model with those of
some of the existing models in the time series literature.