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.
"Sinopsis" puede pertenecer a otra edición de este libro.
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.
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.
"Sobre este título" puede pertenecer a otra edición de este libro.
Librería: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Alemania
Taschenbuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -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. 260 pp. Englisch. Nº de ref. del artículo: 9783659389801
Cantidad disponible: 2 disponibles
Librería: moluna, Greven, Alemania
Condición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Ramanjineyulu B.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. Nº de ref. del artículo: 5153041
Cantidad disponible: Más de 20 disponibles
Librería: Books Puddle, New York, NY, Estados Unidos de America
Condición: New. pp. 260. Nº de ref. del artículo: 26128812112
Cantidad disponible: 4 disponibles
Librería: Majestic Books, Hounslow, Reino Unido
Condición: New. Print on Demand pp. 260 2:B&W 6 x 9 in or 229 x 152 mm Perfect Bound on Creme w/Gloss Lam. Nº de ref. del artículo: 131742607
Cantidad disponible: 4 disponibles
Librería: preigu, Osnabrück, Alemania
Taschenbuch. Condición: Neu. Statistical Inference in Autoregressive Models | Estimation of Autoregressive Models | B. Ramanjineyulu (u. a.) | Taschenbuch | 260 S. | Englisch | 2013 | LAP LAMBERT Academic Publishing | EAN 9783659389801 | Verantwortliche Person für die EU: BoD - Books on Demand, In de Tarpen 42, 22848 Norderstedt, info[at]bod[dot]de | Anbieter: preigu. Nº de ref. del artículo: 105711578
Cantidad disponible: 5 disponibles
Librería: buchversandmimpf2000, Emtmannsberg, BAYE, Alemania
Taschenbuch. Condición: Neu. This item is printed on demand - Print on Demand Titel. Neuware -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.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 260 pp. Englisch. Nº de ref. del artículo: 9783659389801
Cantidad disponible: 1 disponibles
Librería: Biblios, Frankfurt am main, HESSE, Alemania
Condición: New. PRINT ON DEMAND pp. 260. Nº de ref. del artículo: 18128812122
Cantidad disponible: 4 disponibles
Librería: AHA-BUCH GmbH, Einbeck, Alemania
Taschenbuch. Condición: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - 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. Nº de ref. del artículo: 9783659389801
Cantidad disponible: 1 disponibles