The process of estimating the parameters of regression model is still one of important subjects despite of large number of papers and studies written in this subject which differ in techniques followed in the process of estimation. In the present work, we discuss the classical nonparametric estimation methods, some robust estimation methods "least absolute deviations, M-estimation and trimmed least squares" and two suggested methods "depending upon nonparametric and M-estimation" with the OLS estimation method.
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The process of estimating the parameters of regression model is still one of important subjects despite of large number of papers and studies written in this subject which differ in techniques followed in the process of estimation. In the present work, we discuss the classical nonparametric estimation methods, some robust estimation methods "least absolute deviations, M-estimation and trimmed least squares" and two suggested methods "depending upon nonparametric and M-estimation" with the OLS estimation method.
Assit. Prof. Dr. Nadia Hashim Al-Noor, Ph.D. in Mathematical Statistics, Department of Mathematics, College of Science, AL-Mustansiriyah University, Baghdad, Iraq.
"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 -The process of estimating the parameters of regression model is still one of important subjects despite of large number of papers and studies written in this subject which differ in techniques followed in the process of estimation. In the present work, we discuss the classical nonparametric estimation methods, some robust estimation methods 'least absolute deviations, M-estimation and trimmed least squares' and two suggested methods 'depending upon nonparametric and M-estimation' with the OLS estimation method. 56 pp. Englisch. Nº de ref. del artículo: 9783659926914
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Condición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Hashim Al-Noor NadiaAssit. Prof. Dr. Nadia Hashim Al-Noor, Ph.D. in Mathematical Statistics, Department of Mathematics, College of Science, AL-Mustansiriyah University, Baghdad, Iraq.The process of estimating the parameters of re. Nº de ref. del artículo: 158877861
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Librería: buchversandmimpf2000, Emtmannsberg, BAYE, Alemania
Taschenbuch. Condición: Neu. This item is printed on demand - Print on Demand Titel. Neuware -The process of estimating the parameters of regression model is still one of important subjects despite of large number of papers and studies written in this subject which differ in techniques followed in the process of estimation. In the present work, we discuss the classical nonparametric estimation methods, some robust estimation methods 'least absolute deviations, M-estimation and trimmed least squares' and two suggested methods 'depending upon nonparametric and M-estimation' with the OLS estimation method.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 56 pp. Englisch. Nº de ref. del artículo: 9783659926914
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Librería: AHA-BUCH GmbH, Einbeck, Alemania
Taschenbuch. Condición: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - The process of estimating the parameters of regression model is still one of important subjects despite of large number of papers and studies written in this subject which differ in techniques followed in the process of estimation. In the present work, we discuss the classical nonparametric estimation methods, some robust estimation methods 'least absolute deviations, M-estimation and trimmed least squares' and two suggested methods 'depending upon nonparametric and M-estimation' with the OLS estimation method. Nº de ref. del artículo: 9783659926914
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Librería: preigu, Osnabrück, Alemania
Taschenbuch. Condición: Neu. Some Methods of Robust Regression Model | Nadia Hashim Al-Noor (u. a.) | Taschenbuch | 56 S. | Englisch | 2016 | LAP LAMBERT Academic Publishing | EAN 9783659926914 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu. Nº de ref. del artículo: 103480424
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