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**Statistical models and methods for lifetime data.**
*(English)*
Zbl 0541.62081

Wiley Series in Probability and Mathematical Statistics. New York etc.: John Wiley & Sons. XI, 580 p. (1982).

According to the author: ”This book is an attempt to draw together some of the basic statistical methods of analyzing lifetime data. The specific techniques and models that underlie them are emphasized over any particular area of application.” He has been successful in achieving this aim.

The book is divided into ten chapters and some appendices. Chapter 1 contains introductory material on lifetime distributions and surveys the most important parametric models. Chapter 2 discusses nonparametric estimation of the survivor function and certain plotting procedures. Chapters 3,4 and 5 deal with parametric inference for important models, including the exponential, Weibull, gamma, log-normal and generalized gamma distributions. Parametric regression models based on these distributions are discussed in Chapter 6.

The next two chapters present nonparametric and distribution free procedures: the former deal with methods based on Cox’s proportional hazards regression model and the latter give distribution free procedures for single- and many sample procedures.

Chapter 9 presents some goodness-of-fit tests and finally Chapter 10 contains a brief discussion of some multivariate and stochastic processes models. Numerical illustrations are given for most inference procedures. An extensive set of references on lifetime data methodology is also included.

The book is divided into ten chapters and some appendices. Chapter 1 contains introductory material on lifetime distributions and surveys the most important parametric models. Chapter 2 discusses nonparametric estimation of the survivor function and certain plotting procedures. Chapters 3,4 and 5 deal with parametric inference for important models, including the exponential, Weibull, gamma, log-normal and generalized gamma distributions. Parametric regression models based on these distributions are discussed in Chapter 6.

The next two chapters present nonparametric and distribution free procedures: the former deal with methods based on Cox’s proportional hazards regression model and the latter give distribution free procedures for single- and many sample procedures.

Chapter 9 presents some goodness-of-fit tests and finally Chapter 10 contains a brief discussion of some multivariate and stochastic processes models. Numerical illustrations are given for most inference procedures. An extensive set of references on lifetime data methodology is also included.

Reviewer: V.P.Gupta

### MSC:

62N05 | Reliability and life testing |

62-02 | Research exposition (monographs, survey articles) pertaining to statistics |

62F10 | Point estimation |

62G05 | Nonparametric estimation |