Statistical Inference in Autoregressive Models

In this book,an attempt has been made by developing some inferential methods for autoregressive models by using Internally studentized residuals.In the Applied regression analysis, the autoregressive models, moving average models and combined autoregressive and moving average models have a wide number applications. The study on autoregressive process/models is considered to be essential to both the theoretical and applied statisticians.The first order and higher order autoregressive models for regressed variable and errors have been described by giving auto covariance functions.Further,an autoregressive dynamic model without constant term has been specified and in the presence of lagged dependent variable, a modified durbin's h-statistic for testing the hypthesis of no auto correlation has been developed for first order autoregressive error process, Instrumental variable method of estimation has been proposed to estimate the parameters of first order autoregressive errors model with lagged dependent variable as regressor and hence obtained estimates for autocorrelation co-efficients based an Internally studentized residuals.

Autorentext

Mr. Bandi. Ramanjineyulu Working as a Business Analyst in Tata Consultancy Services at Bangalore, Karnataka, INDIA.He has 2 Years of Analytics Experience and 1 year of teaching experience. He has published 3 papers in National/ International Journals and 6 Research Papers were presented at National/International Seminar/Conferences.