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Nonparametric Inference for a Partially Observed Compartmental Process
Author(s) -
Becker Niels,
Yip Paul
Publication year - 1987
Publication title -
australian journal of statistics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.434
H-Index - 41
eISSN - 1467-842X
pISSN - 0004-9581
DOI - 10.1111/j.1467-842x.1987.tb00730.x
Subject(s) - unobservable , nonparametric statistics , transient (computer programming) , inference , observable , statistic , hazard ratio , econometrics , hazard , statistics , mathematics , statistical physics , physics , computer science , chemistry , confidence interval , artificial intelligence , organic chemistry , quantum mechanics , operating system
Summary Methods of nonparametric inference are proposed for a process with two transient and three absorbing states. It is assumed that the time of transitions between the transient states are unobservable. One area of applications is in epidemiology where the transient states correspond to healthy and ill, while the absorbing states correspond to types of death. It is the onset of illness which is not observable. An estimate is given for a cumulative hazard rate between the transient states, the exit hazard rates are estimated at a specific point in time and a statistic for comparing exit rates from the transient states is given.