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Mathematical and Statistical Models and Methods in Reliability

Applications to Medicine, Finance, and Quality Control

  • Book
  • © 2010

Overview

Editors:
  1. V.V. Rykov

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

  2. N. Balakrishnan

    1. McMaster University, Department of Mathematics and Statistics, Hamilton, Canada

  3. M.S. Nikulin

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

  • 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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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.

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Table of contents (33 chapters)

  1. Front Matter

    Pages i-xxvi
    Download chapter PDF

  2. Reliability Models, Methods, and Optimization

    1. Front Matter

      Pages 1-1
      Download chapter PDF

    2. Reliability of Semi-Markov Systems with Asymptotic Merging Phase Space

      • V. S. Koroliuk, N. Limnios
      Pages 3-18

    3. Nonlinearly Perturbed Stochastic Processes and Systems

      • Dmitrii S. Silvestrov
      Pages 19-37

    4. On a Copula for Failure Times of System Elements

      • Alexander Andronov
      Pages 39-50

    5. On One Method of Reliability Coefficients Calculation for Objects in Non-Homogeneous Event Flows

      • Alexander Antonov, Kristina Belova, Valeriy Chepurko
      Pages 51-67

    6. A New Approach to Maintenance Optimization by Modeling Intensity Control

      • Reza Ahmadi, Martin Newby
      Pages 69-85

    7. Longitudinal Latent Markov Processes Observable Through an Invariant Rasch Model

      • Moussedek Bousseboua, Mounir Mesbah
      Pages 87-100

    8. Dynamics of Dependence Properties for Lifetimes Influenced by Unobservable Environmental Factors

      • Rachele Foschi, Fabio Spizzichino
      Pages 101-112

    9. On Alternative of Choice for a Prophylaxis Problem

      • B. P. Harlamov
      Pages 113-122

    10. Optimal Incomplete Maintenance for Systems with Discrete Time-to-Failure Distribution

      • Waltraud Kahle
      Pages 123-132

    11. A Gini-Type Index for Aging/Rejuvenating Objects

      • M. P. Kaminskiy, V. V. Krivtsov
      Pages 133-140

    12. Redundancy Analysis for Multi-state System: Reliability and Financial Assessment

      • Anatoly Lisnianski, Yi Ding
      Pages 141-157

    13. On the Reliability Modeling of Hierarchical Systems

      • Vladimir Rykov, Dmitry Kozyrev
      Pages 159-174

  3. Statistical Methods in Reliability

    1. Front Matter

      Pages 175-175
      Download chapter PDF

    2. Parametric Estimation of Redundant System Reliability From Censored Data

      • Vilijandas Bagdonavičius, Inga Masiulaitytė, Mikhail Nikulin
      Pages 177-191

    3. Assessing Accuracy of Statistical Inferences by Resamplings

      • Yuri K. Belyaev
      Pages 193-206

    4. Change Point Estimation in Regression Models with Fixed Design

      • Maik Döring, Uwe Jensen
      Pages 207-221

    5. A Model for Field Failure Prediction Using Dynamic Environmental Data

      • Yili Hong, William Q. Meeker
      Pages 223-233

    6. Efficient Regression Estimation Under General Censoring and Truncation

      • Catherine Huber
      Pages 235-241
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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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