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Birkhäuser
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Mathematical and Statistical Models and Methods in Reliability

Applications to Medicine, Finance, and Quality Control

  • Book
  • © 2010

Overview

  • Real-world applications to survival analysis, aging, lifetime data analysis, artificial intelligence, medicine, carcinogenesis studies, nuclear power, financial modeling, aircraft engineering, quality control, and transportation
  • Chapters are written by recognized experts in reliability
  • For a broad audience of researchers and practitioners in applied probability and statistics and a variety of related fields
  • Includes supplementary material: sn.pub/extras

Part of the book series: Statistics for Industry and Technology (SIT)

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Table of contents (33 chapters)

  1. Reliability Models, Methods, and Optimization

  2. Statistical Methods in Reliability

Keywords

About this book

An outgrowth of the sixth conference on “Mathematical Methods in Reliability: Theory, Methods, and Applications,” this book is a selection of invited chapters, all of which deal with various aspects of mathematical and statistical models and methods in reliability.

Written by recognized experts in the field of reliability, the contributions cover a wide range of models, methods, and applications, reflecting recent developments in areas such as survival analysis, aging, lifetime data analysis, artificial intelligence, medicine, carcinogenesis studies, nuclear power, financial modeling, aircraft engineering, quality control, and transportation.

The volume is thematically organized into four major sections:

* Reliability Models, Methods, and Optimization;

* Statistical Methods in Reliability;

* Applications;

* Computer Tools for Reliability.

Mathematical and Statistical Models and Methods in Reliability is an excellent reference text for researchers and practitioners in applied probability and statistics, industrial statistics, engineering, medicine, finance, transportation, the oil and gas industry, and artificial intelligence.

Editors and Affiliations

  • Department of Applied Mathematics, Gubkin Russian State University of Oil a, Moskva, Russian Federation

    V.V. Rykov

  • McMaster University, Department of Mathematics and Statistics, Hamilton, Canada

    N. Balakrishnan

  • Université Victor Segalen Bordeaux 2, I’lnstitut de Mathématiques de Bordeaux, Bordeaux Cedex, France

    M.S. Nikulin

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