Análise de sensibilidade e resíduos em modelos de regressão com respostas bivariadas por meio de cópulas

Gomes, Eduardo Monteiro de Castro

doi:10.11606/d.11.2008.tde-25032008-151751

Cited by 1 publication

(3 citation statements)

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“…For the bivariate regression model with cure fraction, the maximum-likelihood estimate (MLE) θ of θ under constraints on the parameters can be calculated numerically by maximizing the loglikelihood function (8). We use the statistical software package R to computeθ.…”

Section: Inference Methodsmentioning

confidence: 99%

“…The Archimedean copula family is associated with bivariate survival models. For this reason, we consider the Clayton copula, which has given good results in recent works, for example, [7,8]. In the context of copulas, some works can be cited (e.g.…”

Section: Introductionmentioning

confidence: 99%

“…[9,10]) to study estimation procedures. Tibaldi [11] and Núñez [12] proposed marginal models for proportional hazards, and He and Lawless [13] and Gomes [8] used marginal location-scale models.…”

Section: Introductionmentioning

confidence: 99%

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A bivariate regression model with cure fraction

Fachini

Ortega

Cordeiro

2013

Journal of Statistical Computation and Simulation

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The use of bivariate distributions plays a fundamental role in survival and reliability studies. In this paper, we introduce a location-scale model for bivariate survival times based on the copula to model the dependence of bivariate survival data with cure fraction. We create the correlation structure between the failure times using the Clayton family of copulas, which is assumed to have any distribution. It turns out that the model becomes very flexible with respect to the choice of the marginal distributions. For the proposed model, we consider inferential procedures based on constrained parameters under maximum likelihood. We derive the appropriate matrices for assessing local influence under different perturbation schemes and present some ways to perform global influence analysis. The relevance of the approach is illustrated using a real data set and a diagnostic analysis is performed to select an appropriate model.

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Section: Inference Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%