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The FGM bivariate lifetime copula model: a bayesian approach
(2011)
In this paper, we propose a bivariate distribution for the bivariate survival times based on Farlie-Gumbel-Morgenstern copula to model the dependence on a bivariate survival data. The proposed model allows for the presence ...
Influence Assessment in an Heteroscedastic Errors-in-Variables Model
(TAYLOR & FRANCIS INC, 2012)
The main goal of this article is to consider influence assessment in models with error-prone observations and variances of the measurement errors changing across observations. The techniques enable to identify potential ...
Influence analysis for the generalized Waring regression model
(TAYLOR & FRANCIS LTD, 2020)
In this paper, we consider a regression model under the generalized Waring distribution for modeling count data. We develop and implement local influence diagnostic techniques based on likelihood displacement. Also we ...
Influence Assessment in an Heteroscedastic Errors-in-Variables Model
(Taylor and Francis Group, LLCPhiladelphia, 2012)
The main goal of this article is to consider influence assessment in models with error-prone observations and variances of the measurement errors changing across observations. The techniques enable to identify potential ...
The log-Weibull-negative-binomial regression model under latent failure causes and presence of randomized activation schemes
(Taylor and FrancisPhiladelphia, 2015-08)
The purpose of this paper is to develop a Bayesian approach for the log-Weibull-negative-binomial regression
model under latent failure causes and presence of a randomized activation mechanism. We assume
the number of ...
Estimation and diagnostics for heteroscedastic nonlinear regression models based on scale mixtures of skew-normal distributions
(ELSEVIER SCIENCE BVAMSTERDAM, 2012)
An extension of some standard likelihood based procedures to heteroscedastic nonlinear regression models under scale mixtures of skew-normal (SMSN) distributions is developed. This novel class of models provides a useful ...