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Partially linear censored regression models using heavy-tailed distributions: A Bayesian approach
(ELSEVIER SCIENCE BV, 2014)
Linear regression models where the response variable is censored are often considered in statistical analysis. A parametric relationship between the response variable and covariates and normality of random errors are ...
Measuring time series predictability using support vector regression
(TAYLOR & FRANCIS INC, 2008)
Most studies involving statistical time series analysis rely on assumptions of linearity, which by its simplicity facilitates parameter interpretation and estimation. However, the linearity assumption may be too restrictive ...
Bayesian non-linear regression models with skew-elliptical errors: Applications to the classification of longitudinal profiles
(ELSEVIER, 2008)
Typically, the fundamental assumption in non-linear regression models is the normality of the errors. Even though this model offers great flexibility for modeling these effects, it suffers from the same lack of robustness ...
Crop yield estimation using satellite images: comparison of linear and non-linear models
(Facultad de Ciencias Agropecuarias., 2018)
Heteroscedastic Nonlinear Regression Models
(TAYLOR & FRANCIS INCNEW YORK, 2010)
In this article, we present a generalization of the Bayesian methodology introduced by Cepeda and Gamerman (2001) for modeling variance heterogeneity in normal regression models where we have orthogonality between mean and ...
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 ...
Influence diagnostics in Gaussian spatial linear models
(TAYLOR & FRANCIS LTD, 2012)
Spatial linear models have been applied in numerous fields such as agriculture, geoscience and environmen-tal sciences, among many others. Spatial dependence structure modelling, using a geostatistical approach,is an ...