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Measures of Departure from Constant Failure Rate Models and Proportional Hazards Rate Models for Grouped Data
Author(s) -
Bhattacharya Bhaskar
Publication year - 1999
Publication title -
biometrical journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.108
H-Index - 63
eISSN - 1521-4036
pISSN - 0323-3847
DOI - 10.1002/(sici)1521-4036(199905)41:2<187::aid-bimj187>3.0.co;2-6
Subject(s) - constant (computer programming) , statistics , failure rate , goodness of fit , mathematics , proportional hazards model , measure (data warehouse) , econometrics , computer science , data mining , programming language
Two measures are proposed to represent the degree of departure from the constant failure rate model of a system when data are grouped. Two measures are also proposed to represent the degree of departure from the proportional hazards rate model when two systems are present and grouped data are considered. In each case one measure is based on the Kullback‐Leibler discrepancy and the other is based on the Pearson χ 2 type discrepancy using the failure rates. The usefulness of the proposed measures are discussed with applications. A simulation study shows that the proposed measures perform no worse than the goodness‐of‐fit tests when testing for the constant failure rate model.