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Transformed generalized linear models
(ELSEVIER SCIENCE BV, 2009)
The estimation of data transformation is very useful to yield response variables satisfying closely a normal linear model, Generalized linear models enable the fitting of models to a wide range of data types. These models ...
Advocating better habitat use and selection models in bird ecology
(Sociedade Brasileira de Ornitologia, 2018-06)
Studies on habitat use and habitat selection represent a basic aspect of bird ecology, due to its importance in natural history, distribution, response to environmental changes, management and conservation. Basically, a ...
Surviving fully Bayesian nonparametric regression models
(Oxford University Press, 2013)
This chapter compares two Bayesian nonparametric models that generalize the accelerated failure time model, based on recent work on probability models for predictor-dependent probability distributions. It begins by reviewing ...
Modelos para séries temporais utilizando as distribuições normal generalizada e log-normal generalizada
(Universidade Federal de São CarlosUFSCarPrograma de Pós-Graduação em Estatística - PPGEsCâmpus São Carlos, 2016-03-23)
From the generalized normal distribution and concepts of the generalized autoregressive
moving averages models we introduce the generalized normal-ARMA model as
an alternative way to model time series exhibiting symmetry ...
Linear and Poisson models for genetic evaluation of tick resistance in cross-bred Hereford x Nellore cattle
(2013-04-15)
Cattle resistance to ticks is measured by the number of ticks infesting the animal. The model used for the genetic analysis of cattle resistance to ticks frequently requires logarithmic transformation of the observations. ...
Linear and Poisson models for genetic evaluation of tick resistance in cross-bred Hereford x Nellore cattle
(2013-04-15)
Cattle resistance to ticks is measured by the number of ticks infesting the animal. The model used for the genetic analysis of cattle resistance to ticks frequently requires logarithmic transformation of the observations. ...
Weak nondifferential measurement error models
(ELSEVIER SCIENCE BV, 1998)
In this note we consider the class of weak nondifferential measurement error models, which as a special case, contains the class of the nondifferential measurement error models (Carroll et al., 1995). Examples of measurement ...
Modeling variability in generalized linear models
This work proposes joint modeling of parameters in the biparametric exponential family, including heteroscedastic linear regression (non linear regression) models; with joint modeling of the mean and precision (the ...
Bayesian inference and diagnostics in zero-inflated generalized power series regression model
(Taylor & Francis Inc, 2016-01-01)
The paper provides a Bayesian analysis for the zero-inflated regression models based on the generalized power series distribution. The approach is based on Markov chain Monte Carlo methods. The residual analysis is discussed ...