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, Student-t, 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 semi-parametric models, where both location and dispersion parameters of the response variable distribution include non-parametric additive components described by using B-splines; 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 non-parametric components approximated by using B-splines.

Install the latest version of this package by entering the following in R:

`install.packages("BayesGESM")`

Author | Luz Marina Rondon <lumarp@gmail.com> and Heleno Bolfarine |

Date of publication | 2015-06-06 07:50:04 |

Maintainer | Luz Marina Rondon <lumarp@gmail.com> |

License | GPL-2 | GPL-3 |

Version | 1.4 |

**BayesGESM-package:** Bayesian Analysis of Generalized Elliptical Semi-Parametric...

**bsp:** Tool to approximate smooth functions by B-splines.

**bsp.graph.fmem:** Tool for plotting the nonlinear effects that are approximated...

**bsp.graph.gesm:** Tool for plotting the nonlinear effects that are approximated...

**fmem:** Flexible Measurement Error Models

**gesm:** Generalized Elliptical Semi-parametric Models

**mcmc.fmem:** MCMC algorithm for Flexible Measurement Error Models

**mcmc.gesm:** MCMC algorithm for Generalized Elliptical Semi-parametric...

**summary.fmem:** Produces a complete summary of flexible measurement error...

**summary.gesm:** Produces a complete summary of Generalized elliptical...

**TexasData:** Relationship between income and demographic composition in...

NAMESPACE

data

data/TexasData.rda

R

R/mcmc.fmem.R
R/bsp.R
R/fmem.R
R/summary.fmem.R
R/gesm.R
R/BayesGESM-internal.R
R/bsp.graph.fmem.R
R/mcmc.gesm.R
R/bsp.graph.gesm.R
R/summary.gesm.R
MD5

DESCRIPTION

man

man/gesm.Rd
man/summary.fmem.Rd
man/fmem.Rd
man/BayesGESM-package.Rd
man/TexasData.Rd
man/bsp.graph.gesm.Rd
man/bsp.graph.fmem.Rd
man/mcmc.gesm.Rd
man/bsp.Rd
man/summary.gesm.Rd
man/mcmc.fmem.Rd
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