Statistical Models and Methods for Reliability and Survival Analysis

by Couallier , Vincent; Gerville-Ré; ache, Lé; o; Huber-Carol, Catherine; Limnios, Nikolaos; Mesbah, Mounir

• ISBN13: 9781848216198
• ISBN10: 184821619X
• Edition: 1st
• Format: Hardcover
• Copyright: 2013-12-31
• Publisher: Wiley-ISTE

Summary

Statistical Models and Methods for Reliability and Survival Analysis brings together contributions by specialists in statistical theory as they discuss their applications providing up-to-date developments in methods used in survival analysis, statistical goodness of fit, stochastic processes for system reliability, amongst others. Many of these are related to the work of Professor M. Nikulin in statistics over the past 30 years. The authors gather together various contributions with a broad array of techniques and results, divided into three parts - Statistical Models and Methods, Statistical Models and Methods in Survival Analysis, and Reliability and Maintenance.

The book is intended for researchers interested in statistical methodology and models useful in survival analysis, system reliability and statistical testing for censored and non-censored data.

Author Biography

Vincent Couallier is Associate Professor at Bordeaux Segalen University in France

Léo Gerville-Réache is Associate Professor at Bordeaux 2 University in France.

Catherine Huber-Carol is Professor Emeritus at Paris René Descartes University in France.

Nikolaos Limnios is Professor at Compiègne University of Technology in France.

Mounir Mesbah is Professor at University Pierre and Marie Curie in Paris, France.

Table of Contents

Part A : Statistical models and Methods

1. Zhezhen J. and Mesbah M. : Statistical methods for the evaluation of agreement

2. George F. and Gulati S. : A Universal Goodness of Fit Test based on Regression Techniques

3. Karagrigoriou A.,  Makrides A. and Vonta I.  : On goodness of fit tests for heavy-tailed distributions

4. Androulakis E., Koukouvinos C. and Vonta F. : On penalized likelihood with applications

5. Lemeshko B., Lemeshko S. and Rogozhnikov A. : Interactive investigation of statistical regularities in testing composite hypotheses of goodness-of-fit

6. Broniatowski M. and Caron V. : Conditional inference in parametric models

7. Laüter H. : Modeling of Categorical Data

8. Martynov G. : Decompositions for some Gaussian processes and Durbin-Knott components of Cramér- von Mises test

9. Kutoyants Y. and  Zhou L. : On Construction of GoF Tests with Simple and Composite Basic Hypothesis for Ergodic Diffusion Processes.

Part B : Statistical models and Methods in Survival Analysis

1. Brunel E., Comte F. and Guilloux A. : Imputation versus Estimation strategies for missing data in survival analysis

2. Saint-pierre P. and Lopez O. : Nonparametric estimation of linear functionals of a multivariate distribution under multivariate censoring with applications.

3. Solev V. : A minimum distance estimator under censoring.

4. Lemeshko B. and Chimitova E. : A Comparative Analysis of Some Chi-squared Goodness-of-Fit Tests for Censored Data

5. Dupuy JP. Mezaouer A. and Boukhetala K. : A nonparametric test for comparing treatments with missing data and dependent censoring

Part C : Reliability and Maintenance

1. Kahle W. : Incomplete maintenance in degradation processes

2. Shi Y. and Meeker W. : Planning Accelerated Destructive Degradation Test with Competing Risks

3. Bagdonavicius V. : Goodness-of-fit for redundant systems models

4. Paroissin C. and Rabehasaina L. : Time-to-failure of Markov modulated gamma process, with application to replacement policies

5. Antonov A., Plyaskin A. and Tataev K. : Calculation of the redundant structures reliability for aging elements

6. Bouzebda S. and Limnios N. : Some asymptotic results for weighted bootstraps of the empirical estimator of a semi-Markov kernel with applications

7. Fatemi F., Saintis L. and Guérin F. : Accelerated testing planning : optimization, robustness and analysis

8. Rykov V. : On engineering risks of complex hierarchical systems analysis