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Lifetime Data : Statistical Models and Methods - Jayant V Deshpande

Lifetime Data

Statistical Models and Methods

By: Jayant V Deshpande, Sudha G Purohit

eText | 15 December 2015 | Edition Number 2

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This book is meant for postgraduate modules that cover lifetime data in reliability and survival analysis as taught in statistics, engineering statistics and medical statistics courses. It is helpful for researchers who wish to choose appropriate models and methods for analyzing lifetime data. There is an extensive discussion on the concept and role of ageing in choosing appropriate models for lifetime data, with a special emphasis on tests of exponentiality. There are interesting contributions related to the topics of ageing, tests for exponentiality, competing risks and repairable systems. A special feature of this book is that it introduces the public domain R-software and explains how it can be used in computations of methods discussed in the book.

This new edition includes new sections on Frailty Models and Accelerated Life Time Models. Many more illustrations and exercises are also included.

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This book is meant for postgraduate modules that cover lifetime data in reliability and survival analysis as taught in statistics, engineering statistics and medical statistics courses. It is helpful for researchers who wish to choose appropriate models and methods for analyzing lifetime data. There is an extensive discussion on the concept and role of ageing in choosing appropriate models for lifetime data, with a special emphasis on tests of exponentiality. There are interesting contributions related to the topics of ageing, tests for exponentiality, competing risks and repairable systems. A special feature of this book is that it introduces the public domain R-software and explains how it can be used in computations of methods discussed in the book.

This new edition includes new sections on Frailty Models and Accelerated Life Time Models. Many more illustrations and exercises are also included.

Request Inspection Copy


Readership: Graduate students in probability and statistics, decision sciences, bioinformatics and industrial engineering.
Key Features:
  • Special emphasis on ageing and tests of exponentiality and their role in choosing appropriate models for lifetime data
  • Extensive discussion of classical parametric and nonparametric models and relevant inference
  • Documentation of new results in ageing, testing for competing risks and repairable systems
  • Introduction and application of the public domain R-software in computations of methods discussed in the book
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