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Estimation of Parameters of the Two-Parameter Rayleigh Distribution: Based on Progressive Type-II Censoring using the Newton-Raphson (NR) and the Expectation Maximation (EM) Algorithms - Softcover
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Estimation of Parameters of the Two-Parameter Rayleigh Distribution
Verlag:
LAP LAMBERT Academic Publishing, 2019
ISBN 10: 6202197471
ISBN 13: 9786202197472
Neu
Softcover
Anbieter: Books Puddle, New York, NY, USA
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Estimation of Parameters of the Two-Parameter Rayleigh Distribution
Verlag:
LAP LAMBERT Academic Publishing Okt 2019, 2019
ISBN 10: 6202197471
ISBN 13: 9786202197472
Neu
Taschenbuch
Anbieter: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Deutschland
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Taschenbuch. Zustand: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -In this book, Maximum likelihood estimates for the shape and scale parameters of Two- Parameters Rayleigh distribution are obtained based on progressive type-II censored samples using the Newton-Raphson (NR) method and the Expectation-maximization (EM) algorithm. A simple algorithm of Balakrishnan and Sandhu (1995) and Aggarwala and Balakrishnan (2000) is used for generating progressive type-II censored samples. Based on this censoring scheme, approximate asymptotic variances are derived and used to construct approximate confidence intervals of the parameters. The performance of these two maximum likelihood estimation methods is compared through simulation results of biases, root mean squared error (RMSE), and the coverage rate. Simulation results showed that in nearly all the combination of simulation conditions the estimators based on the EM algorithm have small biases, small variances, the small root of mean squared error, and narrower widths of confidence intervals compared to those obtained using the NR method. Finally, two illustrative examples with real-life data sets are provided to illustrate how maximum likelihood estimation using the two algorithms works in practice. 76 pp. Englisch. Bestandsnummer des Verkäufers 9786202197472
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Estimation of Parameters of the Two-Parameter Rayleigh Distribution
Verlag:
LAP LAMBERT Academic Publishing, 2019
ISBN 10: 6202197471
ISBN 13: 9786202197472
Neu
Softcover
Anbieter: Majestic Books, Hounslow, Vereinigtes Königreich
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Zustand: New. Print on Demand. Bestandsnummer des Verkäufers 395315643
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Estimation of Parameters of the Two-Parameter Rayleigh Distribution
Verlag:
LAP LAMBERT Academic Publishing, 2019
ISBN 10: 6202197471
ISBN 13: 9786202197472
Neu
Softcover
Anbieter: Biblios, Frankfurt am main, HESSE, Deutschland
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Zustand: New. PRINT ON DEMAND. Bestandsnummer des Verkäufers 18401061486
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Estimation of Parameters of the Two-Parameter Rayleigh Distribution
Verlag:
LAP LAMBERT Academic Publishing, 2019
ISBN 10: 6202197471
ISBN 13: 9786202197472
Neu
Softcover
Anbieter: moluna, Greven, Deutschland
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Zustand: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Njenga Dr. GachangiDr. Gachangi Njenga and Mr. Muriithi Daniel - Department of Statistics and Actuarial Science, Kenyatta University, Nairobi, KENYA.In this book, Maximum likelihood estimates for the shape and scale parameters of. Bestandsnummer des Verkäufers 335815387
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Estimation of Parameters of the Two-Parameter Rayleigh Distribution
Verlag:
LAP LAMBERT Academic Publishing Okt 2019, 2019
ISBN 10: 6202197471
ISBN 13: 9786202197472
Neu
Taschenbuch
Anbieter: buchversandmimpf2000, Emtmannsberg, BAYE, Deutschland
Verkäuferbewertung 5 von 5 Sternen
Taschenbuch. Zustand: Neu. Neuware -In this book, Maximum likelihood estimates for the shape and scale parameters of Two- Parameters Rayleigh distribution are obtained based on progressive type-II censored samples using the Newton-Raphson (NR) method and the Expectation-maximization (EM) algorithm. A simple algorithm of Balakrishnan and Sandhu (1995) and Aggarwala and Balakrishnan (2000) is used for generating progressive type-II censored samples. Based on this censoring scheme, approximate asymptotic variances are derived and used to construct approximate confidence intervals of the parameters. The performance of these two maximum likelihood estimation methods is compared through simulation results of biases, root mean squared error (RMSE), and the coverage rate. Simulation results showed that in nearly all the combination of simulation conditions the estimators based on the EM algorithm have small biases, small variances, the small root of mean squared error, and narrower widths of confidence intervals compared to those obtained using the NR method. Finally, two illustrative examples with real-life data sets are provided to illustrate how maximum likelihood estimation using the two algorithms works in practice.Books on Demand GmbH, Überseering 33, 22297 Hamburg 76 pp. Englisch. Bestandsnummer des Verkäufers 9786202197472
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Estimation of Parameters of the Two-Parameter Rayleigh Distribution : Based on Progressive Type-II Censoring using the Newton-Raphson (NR) and the Expectation Maximation (EM) Algorithms
Verlag:
LAP LAMBERT Academic Publishing, 2019
ISBN 10: 6202197471
ISBN 13: 9786202197472
Neu
Taschenbuch
Anbieter: AHA-BUCH GmbH, Einbeck, Deutschland
Verkäuferbewertung 5 von 5 Sternen
Taschenbuch. Zustand: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - In this book, Maximum likelihood estimates for the shape and scale parameters of Two- Parameters Rayleigh distribution are obtained based on progressive type-II censored samples using the Newton-Raphson (NR) method and the Expectation-maximization (EM) algorithm. A simple algorithm of Balakrishnan and Sandhu (1995) and Aggarwala and Balakrishnan (2000) is used for generating progressive type-II censored samples. Based on this censoring scheme, approximate asymptotic variances are derived and used to construct approximate confidence intervals of the parameters. The performance of these two maximum likelihood estimation methods is compared through simulation results of biases, root mean squared error (RMSE), and the coverage rate. Simulation results showed that in nearly all the combination of simulation conditions the estimators based on the EM algorithm have small biases, small variances, the small root of mean squared error, and narrower widths of confidence intervals compared to those obtained using the NR method. Finally, two illustrative examples with real-life data sets are provided to illustrate how maximum likelihood estimation using the two algorithms works in practice. Bestandsnummer des Verkäufers 9786202197472
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