|   | 
Details
   web
Records
Author Celis, P.; de la Cruz, R.; Fuentes, C.; Gomez, HW.
Title Survival and Reliability Analysis with an Epsilon-Positive Family of Distributions with Applications Type
Year 2021 Publication Symmetry-Basel Abbreviated Journal Symmetry
Volume 13 Issue 5 Pages 908
Keywords censored data; EM algorithm; epsilon– exponential distribution; exponential distribution; maximum likelihood; reliability analysis; survival analysis; stress-strength parameter
Abstract 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.
Address
Corporate Author Thesis
Publisher Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 2073-8994 ISBN Medium
Area Expedition Conference
Notes WOS:000654702000001 Approved
Call Number UAI @ alexi.delcanto @ Serial 1384
Permanent link to this record
 

 
Author Leao, J.; Leiva, V.; Saulo, H.; Tomazella, V.
Title Birnbaum-Saunders frailty regression models: Diagnostics and application to medical data Type
Year 2017 Publication Biometrical Journal Abbreviated Journal Biom. J.
Volume 59 Issue 2 Pages 291-314
Keywords Birnbaum-Saunders distribution; Censored data; Global and local influence; Maximum-likelihood method; Residual analysis
Abstract In survival models, some covariates affecting the lifetime could not be observed or measured. These covariates may correspond to environmental or genetic factors and be considered as a random effect related to a frailty of the individuals explaining their survival times. We propose a methodology based on a Birnbaum-Saunders frailty regression model, which can be applied to censored or uncensored data. Maximum-likelihood methods are used to estimate the model parameters and to derive local influence techniques. Diagnostic tools are important in regression to detect anomalies, as departures from error assumptions and presence of outliers and influential cases. Normal curvatures for local influence under different perturbations are computed and two types of residuals are introduced. Two examples with uncensored and censored real-world data illustrate the proposed methodology. Comparison with classical frailty models is carried out in these examples, which shows the superiority of the proposed model.
Address [Leao, Jeremias] Univ Fed Amazonas, Dept Stat, Manaus, Amazonas, Brazil, Email: victorleivasanchez@gmail.com
Corporate Author Thesis
Publisher Wiley Place of Publication Editor
Language English Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 0323-3847 ISBN Medium
Area Expedition Conference
Notes WOS:000396452500006 Approved
Call Number UAI @ eduardo.moreno @ Serial 707
Permanent link to this record