Survival and Reliability Analysis with an Epsilon-Positive Family of Distributions with Applications
Celis
P
author
de la Cruz
R
author
Fuentes
C
author
Gomez
H
W
author
2021
We introduce a new class of distributions called the epsilon-positive family, which can be viewed as generalization of the distributions with positive support. The construction of the epsilon-positive family is motivated by the ideas behind the generation of skew distributions using symmetric kernels. This new class of distributions has as special cases the exponential, Weibull, log-normal, log-logistic and gamma distributions, and it provides an alternative for analyzing reliability and survival data. An interesting feature of the epsilon-positive family is that it can viewed as a finite scale mixture of positive distributions, facilitating the derivation and implementation of EM-type algorithms to obtain maximum likelihood estimates (MLE) with (un)censored data. We illustrate the flexibility of this family to analyze censored and uncensored data using two real examples. One of them was previously discussed in the literature; the second one consists of a new application to model recidivism data of a group of inmates released from the Chilean prisons during 2007. The results show that this new family of distributions has a better performance fitting the data than some common alternatives such as the exponential distribution.
censored data
EM algorithm
epsilon–
exponential distribution
exponential distribution
maximum likelihood
reliability analysis
survival analysis
stress-strength parameter
WOS:000654702000001
exported from refbase (show.php?record=1384), last updated on Wed, 09 Jun 2021 17:12:12 -0400
text
10.3390/sym13050908
Celis_etal2021
Symmetry-Basel
Symmetry
2021
continuing
periodical
academic journal
13
5
908
2073-8994