Set of tools to perform the statistical inference based on the Bayesian approach for regression models under the assumption that independent additive errors follow normal, Studentt, slash, contaminated normal, Laplace or symmetric hyperbolic distributions, i.e., additive errors follow a scale mixtures of normal distributions. The regression models considered in this package are: (i) Generalized elliptical semiparametric models, where both location and dispersion parameters of the response variable distribution include nonparametric additive components described by using Bsplines; and (ii) Flexible measurement error models under the presence of homoscedastic and heteroscedastic random errors, which admit explanatory variables with and without measurement additive errors as well as the presence of a nonparametric components approximated by using Bsplines.
Package details 


Author  Luz Marina Rondon <lumarp@gmail.com> and Heleno Bolfarine 
Date of publication  20150606 07:50:04 
Maintainer  Luz Marina Rondon <lumarp@gmail.com> 
License  GPL2  GPL3 
Version  1.4 
Package repository  View on CRAN 
Installation 
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