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Añadir al carritoGebunden. Condición: New. YAN LIU, PHD, is Principal Reliability Engineer at Medtronic PLC, (USA). She is a certified Master Black Belt at Medtronic and has 12 years of working and consulting experience on reliability engineering and design for Six Sigma.ATHULA I. ABEYRATNE, PHD, is.
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Añadir al carritoBuch. Condición: Neu. Neuware - Demonstrates how to solve reliability problems using practical applications of Bayesian modelsThis self-contained reference provides fundamental knowledge of Bayesian reliability and utilizes numerous examples to show how Bayesian models can solve real life reliability problems. It teaches engineers and scientists exactly what Bayesian analysis is, what its benefits are, and how they can apply the methods to solve their own problems. To help readers get started quickly, the book presents many Bayesian models that use JAGS and which require fewer than 10 lines of command. It also offers a number of short R scripts consisting of simple functions to help them become familiar with R coding.Practical Applications of Bayesian Reliability starts by introducing basic concepts of reliability engineering, including random variables, discrete and continuous probability distributions, hazard function, and censored data. Basic concepts of Bayesian statistics, models, reasons, and theory are presented in the following chapter. Coverage of Bayesian computation, Metropolis-Hastings algorithm, and Gibbs Sampling comes next. The book then goes on to teach the concepts of design capability and design for reliability; introduce Bayesian models for estimating system reliability; discuss Bayesian Hierarchical Models and their applications; present linear and logistic regression models in Bayesian Perspective; and more.\* Provides a step-by-step approach for developing advanced reliability models to solve complex problems, and does not require in-depth understanding of statistical methodology\* Educates managers on the potential of Bayesian reliability models and associated impact\* Introduces commonly used predictive reliability models and advanced Bayesian models based on real life applications\* Includes practical guidelines to construct Bayesian reliability models along with computer codes for all of the case studies\* JAGS and R codes are provided on an accompanying website to enable practitioners to easily copy them and tailor them to their own applicationsPractical Applications of Bayesian Reliability is a helpful book for industry practitioners such as reliability engineers, mechanical engineers, electrical engineers, product engineers, system engineers, and materials scientists whose work includes predicting design or product performance.
Publicado por John Wiley and Sons Ltd, 2019
ISBN 10: 1119287979 ISBN 13: 9781119287971
Idioma: Inglés
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Añadir al carritoHardback. Condición: New. New copy - Usually dispatched within 4 working days. 681.
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Publicado por John Wiley & Sons Inc, New York, 2019
ISBN 10: 1119287979 ISBN 13: 9781119287971
Idioma: Inglés
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Añadir al carritoHardcover. Condición: new. Hardcover. Demonstrates how to solve reliability problems using practical applications of Bayesian models This self-contained reference provides fundamental knowledge of Bayesian reliability and utilizes numerous examples to show how Bayesian models can solve real life reliability problems. It teaches engineers and scientists exactly what Bayesian analysis is, what its benefits are, and how they can apply the methods to solve their own problems. To help readers get started quickly, the book presents many Bayesian models that use JAGS and which require fewer than 10 lines of command. It also offers a number of short R scripts consisting of simple functions to help them become familiar with R coding. Practical Applications of Bayesian Reliability starts by introducing basic concepts of reliability engineering, including random variables, discrete and continuous probability distributions, hazard function, and censored data. Basic concepts of Bayesian statistics, models, reasons, and theory are presented in the following chapter. Coverage of Bayesian computation, Metropolis-Hastings algorithm, and Gibbs Sampling comes next. The book then goes on to teach the concepts of design capability and design for reliability; introduce Bayesian models for estimating system reliability; discuss Bayesian Hierarchical Models and their applications; present linear and logistic regression models in Bayesian Perspective; and more. Provides a step-by-step approach for developing advanced reliability models to solve complex problems, and does not require in-depth understanding of statistical methodologyEducates managers on the potential of Bayesian reliability models and associated impactIntroduces commonly used predictive reliability models and advanced Bayesian models based on real life applicationsIncludes practical guidelines to construct Bayesian reliability models along with computer codes for all of the case studiesJAGS and R codes are provided on an accompanying website to enable practitioners to easily copy them and tailor them to their own applications Practical Applications of Bayesian Reliability is a helpful book for industry practitioners such as reliability engineers, mechanical engineers, electrical engineers, product engineers, system engineers, and materials scientists whose work includes predicting design or product performance. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.
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Añadir al carritoHardcover. Condición: Brand New. har/psc edition. 300 pages. 9.75x7.00x1.00 inches. In Stock.
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Añadir al carritoCondición: New. 2019. 1st Edition. Hardcover. . . . . .
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Añadir al carritoCondición: New. 2019. 1st Edition. Hardcover. . . . . . Books ship from the US and Ireland.
Publicado por John Wiley & Sons Inc, New York, 2019
ISBN 10: 1119287979 ISBN 13: 9781119287971
Idioma: Inglés
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EUR 116,10
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Añadir al carritoHardcover. Condición: new. Hardcover. Demonstrates how to solve reliability problems using practical applications of Bayesian models This self-contained reference provides fundamental knowledge of Bayesian reliability and utilizes numerous examples to show how Bayesian models can solve real life reliability problems. It teaches engineers and scientists exactly what Bayesian analysis is, what its benefits are, and how they can apply the methods to solve their own problems. To help readers get started quickly, the book presents many Bayesian models that use JAGS and which require fewer than 10 lines of command. It also offers a number of short R scripts consisting of simple functions to help them become familiar with R coding. Practical Applications of Bayesian Reliability starts by introducing basic concepts of reliability engineering, including random variables, discrete and continuous probability distributions, hazard function, and censored data. Basic concepts of Bayesian statistics, models, reasons, and theory are presented in the following chapter. Coverage of Bayesian computation, Metropolis-Hastings algorithm, and Gibbs Sampling comes next. The book then goes on to teach the concepts of design capability and design for reliability; introduce Bayesian models for estimating system reliability; discuss Bayesian Hierarchical Models and their applications; present linear and logistic regression models in Bayesian Perspective; and more. Provides a step-by-step approach for developing advanced reliability models to solve complex problems, and does not require in-depth understanding of statistical methodologyEducates managers on the potential of Bayesian reliability models and associated impactIntroduces commonly used predictive reliability models and advanced Bayesian models based on real life applicationsIncludes practical guidelines to construct Bayesian reliability models along with computer codes for all of the case studiesJAGS and R codes are provided on an accompanying website to enable practitioners to easily copy them and tailor them to their own applications Practical Applications of Bayesian Reliability is a helpful book for industry practitioners such as reliability engineers, mechanical engineers, electrical engineers, product engineers, system engineers, and materials scientists whose work includes predicting design or product performance. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
Publicado por John Wiley & Sons Inc, New York, 2019
ISBN 10: 1119287979 ISBN 13: 9781119287971
Idioma: Inglés
Librería: AussieBookSeller, Truganina, VIC, Australia
EUR 166,44
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Añadir al carritoHardcover. Condición: new. Hardcover. Demonstrates how to solve reliability problems using practical applications of Bayesian models This self-contained reference provides fundamental knowledge of Bayesian reliability and utilizes numerous examples to show how Bayesian models can solve real life reliability problems. It teaches engineers and scientists exactly what Bayesian analysis is, what its benefits are, and how they can apply the methods to solve their own problems. To help readers get started quickly, the book presents many Bayesian models that use JAGS and which require fewer than 10 lines of command. It also offers a number of short R scripts consisting of simple functions to help them become familiar with R coding. Practical Applications of Bayesian Reliability starts by introducing basic concepts of reliability engineering, including random variables, discrete and continuous probability distributions, hazard function, and censored data. Basic concepts of Bayesian statistics, models, reasons, and theory are presented in the following chapter. Coverage of Bayesian computation, Metropolis-Hastings algorithm, and Gibbs Sampling comes next. The book then goes on to teach the concepts of design capability and design for reliability; introduce Bayesian models for estimating system reliability; discuss Bayesian Hierarchical Models and their applications; present linear and logistic regression models in Bayesian Perspective; and more. Provides a step-by-step approach for developing advanced reliability models to solve complex problems, and does not require in-depth understanding of statistical methodologyEducates managers on the potential of Bayesian reliability models and associated impactIntroduces commonly used predictive reliability models and advanced Bayesian models based on real life applicationsIncludes practical guidelines to construct Bayesian reliability models along with computer codes for all of the case studiesJAGS and R codes are provided on an accompanying website to enable practitioners to easily copy them and tailor them to their own applications Practical Applications of Bayesian Reliability is a helpful book for industry practitioners such as reliability engineers, mechanical engineers, electrical engineers, product engineers, system engineers, and materials scientists whose work includes predicting design or product performance. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.
Librería: Mispah books, Redhill, SURRE, Reino Unido
EUR 273,79
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Añadir al carritoHardcover. Condición: New. New. book.