Statistical models and methods for lifetime and other time-to-event data are widely used in many fields, including medicine, the environmental sciences, actuarial science, engineering, economics, management, and the social sciences. For example, closely related statistical methods have been applied to the study of the incubation period of diseases such as AIDS, the remission time of cancers, life tables, the time-to-failure of engineering systems, employment duration, and the length of marriages. This volume contains a selection of papers based on the 1994 International Research Conference on Lifetime Data Models in Reliability and Survival Analysis, held at Harvard University. The conference brought together a varied group of researchers and practitioners to advance and promote statistical science in the many fields that deal with lifetime and other time-to-event-data. The volume illustrates the depth and diversity of the field. A few of the authors have published their conference presentations in the new journal Lifetime Data Analysis (Kluwer Academic Publishers).The graph G(m)G(s)|G(s|b = 0); h.f. a#39;idda#39;; p.d.f. ddda#39;, has a decreasing p.d.f. The graph G(i)G(s)G(s|b = 0); h.f. idda#39;; p.d.f. aidda#39;, has an unimodal p.d.f. because the first graph is replaced by G(i). Another possible shape of p.d.f. is dida#39;. To obtainanbsp;...
|Title||:||Lifetime Data: Models in Reliability and Survival Analysis|
|Author||:||Nicholas P. Jewell, Alan C. Kimber, Mei-Ling Ting Lee, G. Alex Whitmore|
|Publisher||:||Springer Science & Business Media - 2013-04-17|