“…valuable to readers seeking an overview of Weibull modelsand…a valuable contribution to libraries…” (Journalof the American Statistical Association, September 2005)
“…may serve as a handbook in research andteaching…” (Zentralblatt Math, Vol.1047, No.22,2004)
“The book is generally well written and easy to read. It couldserve as a useful reference to practitioners…andresearchers.” (Technometrics, November 2004)
“The literature of Weibull models is vast, disjointed, andscattered across many different journals. There are a couple ofbooks devoted solely to the Weibull distribution, but these areoriented toward training and/or consulting purposes. There is nobook that deals with the different Weibull models in an integratedmanner. This book fills that gap.” (Mathematical Reviews,Issue 2004h)
A comprehensive perspective on Weibull models
The literature on Weibull models is vast, disjointed, and scattered across many different journals. Weibull Models is a comprehensive guide that integrates all the different facets of Weibull models in a single volume.
This book will be of great help to practitioners in reliability and other disciplines in the context of modeling data sets using Weibull models. For researchers interested in these modeling techniques, exercises at the end of each chapter define potential topics for future research.
Organized into seven distinct parts, Weibull Models:
- Covers model analysis, parameter estimation, model validation, and application
- Serves as both a handbook and a research monograph. As a handbook, it classifies the different models and presents their properties. As a research monograph, it unifies the literature and presents the results in an integrated manner
- Intertwines theory and application
- Focuses on model identification prior to model parameter estimation
- Discusses the usefulness of the Weibull Probability plot (WPP) in the model selection to model a given data set
- Highlights the use of Weibull models in reliability theory
Filled with in-depth analysis, Weibull Models pulls together the most relevant information on this topic to give everyone from reliability engineers to applied statisticians involved with reliability and survival analysis a clear look at what Weibull models can offer.
From the Back Cover
A comprehensive perspective on Weibull models
The literature on Weibull models is vast, disjointed, and scattered across many different journals. Weibull Models is a comprehensive guide that integrates all the different facets of Weibull models in a single volume.
This book will be of great help to practitioners in reliability and other disciplines in the context of modeling data sets using Weibull models. For researchers interested in these modeling techniques, exercises at the end of each chapter define potential topics for future research.
Organized into seven distinct parts, Weibull Models:
- Covers model analysis, parameter estimation, model validation, and application
- Serves as both a handbook and a research monograph. As a handbook, it classifies the different models and presents their properties. As a research monograph, it unifies the literature and presents the results in an integrated manner
- Intertwines theory and application
- Focuses on model identification prior to model parameter estimation
- Discusses the usefulness of the Weibull Probability plot (WPP) in the model selection to model a given data set
- Highlights the use of Weibull models in reliability theory
Filled with in-depth analysis, Weibull Models pulls together the most relevant information on this topic to give everyone from reliability engineers to applied statisticians involved with reliability and survival analysis a clear look at what Weibull models can offer.
About the Author
D. N. PRABHAKAR MURTHY, PhD, is a Professor of Engineering andOperations Management at the University of Queensland in Brisbane,Australia. He received his PhD in applied mathematics from HarvardUniversity.
MIN XIE, PhD, is an Associate Professor of Industrial andSystems Engineering at the National University of Singapore in KentRidge Crescent, Singapore. He received his PhD in qualitytechnology from Linkoping University in Linkoping, Sweden.
RENYAN JIANG, PhD, is a Professor of Engineering at the ChangshaUniversity of Science and Technology and is also affiliated withthe Department of Mechanical Industrial Engineering at theUniversity of Toronto in Toronto, Ontario, Canada. He received hisPhD in mechanical engineering from the University ofQueensland.
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