Statistical Models Based on Counting Processes

Dados Bibliográficos

ID2872007
AutoresXavier Bry (0000-0003-2546-9860), Per Kragh Andersen (0000-0003-0490-0885), Ornulf Borgan (0000-0002-4687-1202), Richard D Gill (0000-0001-5821-9986), Niels Keiding (0000-0002-6063-721X)
Ano1997
Volume52
Fascículo4
Páginas1046
Data de publicação1997-07-01
Peer ReviewedSim
Open AccessSim
TipoARTICLE
PeriódicoPopulation (JOURNAL)
Identificadores do periódicoISSN: 0032-4663 • E-ISSN: 1957-7966
EditoraJSTOR (PUBLISHER)
DOI10.2307/1534625
OpenAlexW2319384619
IdiomaEN
Citações recebidas56

Modern survival analysis and more general event history analysis may be effectively handled in the mathematical framework of counting processes, stochastic integration, martingale central limit theory and product integration. This book presents this theory, which has been the subject of an intense research activity during the past one-and-a-half decades. The exposition of the theory is integrated with the careful presentation of many practical examples, based almost exlusively on the authors' experience, with detailed numerical and graphical illustrations. Statistical Models Based on Counting Processes may be viewed as a research monograph for mathematical statisticians and biostatisticians, although almost all methods are given in sufficient detail to be used in practice by other mathematically oriented researchers studying event histories (demographers, econometricians, epidemiologists, actuariala mathematicians, reliability engineers, biologists). Much of the material has so far only been available in the journal literature (if at all), and a wide variety of researchers will find this an invlauable survey of the subject

Econometrics · Statistics · Bayesian Methods and Mixture Models · Computer Science · Mathematics · Statistical Distribution Estimation and Applications · Statistical Methods and Inference