Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/11400
Title: On the Weibull-Gamma frailty model, its infinite moments, and its connection to generalized log-logistic, logistic, Cauchy, and extreme-value distributions
Authors: MOLENBERGHS, Geert 
VERBEKE, Geert 
Issue Date: 2011
Publisher: ELSEVIER SCIENCE BV
Source: JOURNAL OF STATISTICAL PLANNING AND INFERENCE, 141 (2). p. 861-868
Abstract: It is shown that the commonly used Weibull-Gamma frailty model has a finite number of finite moments only and that its marginal distribution generalizes the log-logistic distribution. In some cases there is not even a finite variance, and there are cases without a single finite moment. Upon transformation to the entire real line, generalized logistic and generalized Cauchy distributions are introduced and their connection with the previous ones established, as well as with the extreme-value distribution. Apart from intrinsic and classroom value, the family can be of use when formulating non-informative priors in Bayesian data analysis. Also, gauging the amount of finite moments is important when checking regularity conditions in the Weibull-Gamma model. Our findings are illustrated using data from survival in cancer patients. (c) 2010 Elsevier B.B. All rights reserved.
Notes: [Molenberghs, Geert; Verbeke, Geert] Univ Hasselt, Interuniv Inst Biostat & Stat Bioinformat, B-3590 Diepenbeek, Belgium. [Molenberghs, Geert; Verbeke, Geert] Katholieke Univ Leuven, Interuniv Inst Biostat & Stat Bioinformat, B-3000 Leuven, Belgium. geert.molenberghs@uhasselt.be
Keywords: Cauchy distribution; Exponential frailty; Gamma frailty; Weibull model;cauchy distribution; exponential frailty; gamma frailty; Weibull model
Document URI: http://hdl.handle.net/1942/11400
Link to publication/dataset: http://scinet.dost.gov.ph/union/ShowSearchResult.php?s=2&f=&p=&x=&page=&sid=1&id=On+the+Weibull-Gamma+frailty+model%2C+its+infinite+moments%2C+and+its+connection+to+generalized+log-logistic%2C+logistic%2C+Cauchy%2C+and+extreme-value+distributions&Mtype=NONPRINTS
ISSN: 0378-3758
e-ISSN: 1873-1171
DOI: 10.1016/j.jspi.2010.08.008
ISI #: 000284386500025
Rights: (c) 2010 Elsevier B.V. All rights reserved
Category: A1
Type: Journal Contribution
Validations: ecoom 2011
Appears in Collections:Research publications

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