Title of article :
A new long-term lifetime distribution induced by a latent complementary risk framework
Author/Authors :
Francisco Louzada، نويسنده , , Vicente G. Cancho، نويسنده , , Mari Roman&José G. Leite، نويسنده ,
Issue Information :
روزنامه با شماره پیاپی سال 2012
Abstract :
In this paper, we proposed a new three-parameter long-term lifetime distribution induced by a latent
complementary risk framework with decreasing, increasing and unimodal hazard function, the long-term
complementary exponential geometric distribution. The new distribution arises from latent competing risk
scenarios, where the lifetime associated scenario, with a particular risk, is not observable, rather we observe
only the maximum lifetime value among all risks, and the presence of long-term survival. The properties
of the proposed distribution are discussed, including its probability density function and explicit algebraic
formulas for its reliability, hazard and quantile functions and order statistics. The parameter estimation
is based on the usual maximum-likelihood approach. A simulation study assesses the performance of the
estimation procedure.We compare the new distribution with its particular cases, as well as with the longtermWeibull
distribution on three real data sets, observing its potential and competitiveness in comparison
with some usual long-term lifetime distributions.
Keywords :
complementary exponential geometric distribution , latent complementary risks , ovarian cancer data , glioma data , Credit scoring , long-termsurvivals
Journal title :
JOURNAL OF APPLIED STATISTICS
Journal title :
JOURNAL OF APPLIED STATISTICS