glproposal {Bayesiantreg} | R Documentation |
A proposal for degrees of freedom parameter
Description
Propose a value for the degrees of freedom parameter
Usage
glproposal(gl.ini, lambda, p, Maxi, matriz, propuesta, type)
Arguments
gl.ini |
a vector with the previous proposal degrees of freedom parameter |
lambda |
a number indicating the mean parameter value for the Poisson prior an the Poisson proposal. |
p |
a number indicating the parameter value for the Jeffrey's prior an the Jeffrey's proposal. |
Maxi |
a number indicating the maximum value for the uniform prior an the uniforme proposal. |
matriz |
a matrix generate by the function tabla of the bayesiantreg package. |
propuesta |
when type is "D", it is a vector that can take the values of "poi" for a Poisson proposal, "unif" for a uniform proposal or by default the proposal made by Marin and Cepeda (_). When type is "C", it is a vector that can take the values of "exp" for the exponential proposal, "unif" for the uniform proposal, "J2" for the Jeffrey's proposal or by default the proposal made by Marin and Cepeda (_). |
type |
a vector that can take the value "D" if the prior for the degrees of freedom considered as discrete or "C" if it is continuous. |
Details
Generate a proposal for the gamma parameter according to the model proposed by Marin and Cepeda-Cuervo (_).
Value
gl.pro |
a number with the proposal for the degrees of freedom parameter. |
Author(s)
Margarita Marin mmarinj@unal.edu.co, Edilberto Cepeda-Cuervo ecepedac@unal.edu.co
References
1. Marin and Cepeda-Cuervo (_). A Bayesian regression model for the non-standardized t distribution with location, scale and degrees of freedom parameters. Unpublished
2. Cepeda-Cuervo E. (2001). Modelagem da variabilidade em modelos lineares generalizados. Unpublished Ph.D. tesis. Instituto de Matematicas. Universidade Federal do Rio do Janeiro.
3. Cepeda C., E. and Gamerman D. (2001). Bayesian Modeling of Variance Heterogeneity in Normal Regression Models. Brazilian Journal of Probability and Statistics. 14, 207-221