Properties and Inference for Proportional Hazard Models
We consider an arbitrary continuous cumulative distribution function F(x) with a probability density function f(x) = dF(x)/dx and hazard function h f(x)=f(x)/[1-F(x)]. We propose a new family of distributions, the so-called proportional hazard distribution-function, whose hazard function is proporti...
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Universidad Nacional de Colombia
2013-06-01
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doaj-8895fb934e714ee1bf1ca3f85dd94e7d2020-11-25T02:21:26ZengUniversidad Nacional de Colombia Revista Colombiana de Estadística0120-17512013-06-0136195114S0120-17512013000100006Properties and Inference for Proportional Hazard ModelsGUILLERMO MARTÍNEZ-FLÓREZ0GERMÁN MORENO-ARENAS1SANDRA VERGARA-CARDOZO2Universidad de CórdobaUniversidad Industrial de SantanderUniversidad Nacional de ColombiaWe consider an arbitrary continuous cumulative distribution function F(x) with a probability density function f(x) = dF(x)/dx and hazard function h f(x)=f(x)/[1-F(x)]. We propose a new family of distributions, the so-called proportional hazard distribution-function, whose hazard function is proportional to h f(x). The new model can fit data with high asymmetry or kurtosis outside the range covered by the normal, t-student and logistic distributions, among others. We estimate the parameters by maximum likelihood, profile likelihood and the elemental percentile method. The observed and expected information matrices are determined and likelihood tests for some hypotheses of interest are also considered in the proportional hazard normal distribution. We show an application to real data, which illustrates the adequacy of the proposed model.http://www.scielo.org.co/scielo.php?script=sci_arttext&pid=S0120-17512013000100006&lng=en&tlng=enasimetríacurtosisdistribución skew-normalfunción de riesgométodo de los momentosmodelo de riesgo proporcionalverosimilitud perfilada |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
GUILLERMO MARTÍNEZ-FLÓREZ GERMÁN MORENO-ARENAS SANDRA VERGARA-CARDOZO |
spellingShingle |
GUILLERMO MARTÍNEZ-FLÓREZ GERMÁN MORENO-ARENAS SANDRA VERGARA-CARDOZO Properties and Inference for Proportional Hazard Models Revista Colombiana de Estadística asimetría curtosis distribución skew-normal función de riesgo método de los momentos modelo de riesgo proporcional verosimilitud perfilada |
author_facet |
GUILLERMO MARTÍNEZ-FLÓREZ GERMÁN MORENO-ARENAS SANDRA VERGARA-CARDOZO |
author_sort |
GUILLERMO MARTÍNEZ-FLÓREZ |
title |
Properties and Inference for Proportional Hazard Models |
title_short |
Properties and Inference for Proportional Hazard Models |
title_full |
Properties and Inference for Proportional Hazard Models |
title_fullStr |
Properties and Inference for Proportional Hazard Models |
title_full_unstemmed |
Properties and Inference for Proportional Hazard Models |
title_sort |
properties and inference for proportional hazard models |
publisher |
Universidad Nacional de Colombia |
series |
Revista Colombiana de Estadística |
issn |
0120-1751 |
publishDate |
2013-06-01 |
description |
We consider an arbitrary continuous cumulative distribution function F(x) with a probability density function f(x) = dF(x)/dx and hazard function h f(x)=f(x)/[1-F(x)]. We propose a new family of distributions, the so-called proportional hazard distribution-function, whose hazard function is proportional to h f(x). The new model can fit data with high asymmetry or kurtosis outside the range covered by the normal, t-student and logistic distributions, among others. We estimate the parameters by maximum likelihood, profile likelihood and the elemental percentile method. The observed and expected information matrices are determined and likelihood tests for some hypotheses of interest are also considered in the proportional hazard normal distribution. We show an application to real data, which illustrates the adequacy of the proposed model. |
topic |
asimetría curtosis distribución skew-normal función de riesgo método de los momentos modelo de riesgo proporcional verosimilitud perfilada |
url |
http://www.scielo.org.co/scielo.php?script=sci_arttext&pid=S0120-17512013000100006&lng=en&tlng=en |
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