Applied Nonparametric Statistics in Reliability

  • M. Luz Gámiz
  • K. B. Kulasekera
  • Nikolaos Limnios
  • Bo Henry Lindqvist

Part of the Springer Series in Reliability Engineering book series (RELIABILITY)

Table of contents

  1. Front Matter
    Pages i-xiii
  2. Black-Box Approach: Time-to-Failure Analysis

    1. Front Matter
      Pages 1-1
    2. M. Luz Gámiz, K. B. Kulasekera, Nikolaos Limnios, Bo Henry Lindqvist
      Pages 3-29
  3. Grey-Box Approach: Counting Processes

    1. Front Matter
      Pages 31-32
    2. M. Luz Gámiz, K. B. Kulasekera, Nikolaos Limnios, Bo Henry Lindqvist
      Pages 33-64
    3. M. Luz Gámiz, K. B. Kulasekera, Nikolaos Limnios, Bo Henry Lindqvist
      Pages 65-92
    4. M. Luz Gámiz, K. B. Kulasekera, Nikolaos Limnios, Bo Henry Lindqvist
      Pages 93-118
  4. White-Box Approach: The Physical Environment

    1. Front Matter
      Pages 119-120
    2. M. Luz Gámiz, K. B. Kulasekera, Nikolaos Limnios, Bo Henry Lindqvist
      Pages 121-142
    3. M. Luz Gámiz, K. B. Kulasekera, Nikolaos Limnios, Bo Henry Lindqvist
      Pages 143-183
    4. M. Luz Gámiz, K. B. Kulasekera, Nikolaos Limnios, Bo Henry Lindqvist
      Pages 185-225
  5. Back Matter
    Pages 227-230

About this book

Introduction

Nonparametric statistics has probably become the leading methodology for researchers performing data analysis. It is nevertheless true that, whereas these methods have already proved highly effective in other applied areas of knowledge such as biostatistics or social sciences, nonparametric analyses in reliability currently form an interesting area of study that has not yet been fully explored.

Applied Nonparametric Statistics in Reliability is focused on the use of modern statistical methods for the estimation of dependability measures of reliability systems that operate under different conditions. The scope of the book includes:

  • smooth estimation of the reliability function and hazard rate of non-repairable systems;
  • study of stochastic processes for modelling the time evolution of systems when imperfect repairs are performed;
  • nonparametric analysis of discrete and continuous time semi-Markov processes;
  • isotonic regression analysis of the structure function of a reliability system, and
  • lifetime regression analysis.

Besides the explanation of the mathematical background, several numerical computations or simulations are presented as illustrative examples. The corresponding computer-based methods have been implemented using R and MATLAB®. A concrete modelling scheme is chosen for each practical situation and, in consequence, a nonparametric inference procedure is conducted.

Applied Nonparametric Statistics in Reliability will serve the practical needs of scientists (statisticians and engineers) working on applied reliability subjects.

Keywords

Bootstrapping Hazard Regression Repairable System Semi-Markov Model Smooth Estimation

Authors and affiliations

  • M. Luz Gámiz
    • 1
  • K. B. Kulasekera
    • 2
  • Nikolaos Limnios
    • 3
  • Bo Henry Lindqvist
    • 4
  1. 1.Facultad Ciencias, Depto. Estadistica eUniversidad GranadaGranadaSpain
  2. 2., Department of Mathematical SciencesClemson UniversityClemsonUSA
  3. 3., Laboratoire de Mathématiques AppliquéesUniversité de Technologie de CompiègneCompiègneFrance
  4. 4.Technology, Department of Mathematical SciencesNorwegian University of Science andTrondheimNorway

Bibliographic information

  • DOI https://doi.org/10.1007/978-0-85729-118-9
  • Copyright Information Springer-Verlag London Limited 2011
  • Publisher Name Springer, London
  • eBook Packages Engineering
  • Print ISBN 978-0-85729-117-2
  • Online ISBN 978-0-85729-118-9
  • Series Print ISSN 1614-7839
  • About this book