Bayesianbetareg (version 1.2)

gammaproposal: A proposal for gamma parameter

Description

Propose a value for the gamma parameter

Usage

gammaproposal(Y,X, Z, betas, gammas, gpri, Gpri)

Arguments

Y

object of class matrix, with the dependent variable

X

object of class matrix, with the variables for modelling the mean

Z

object of class matrix, with the variables for modelling the variance

betas

a vector with the previous proposal beta parameters

gammas

a vector with the previous proposal gamma parameters

gpri

a vector with the initial values of gamma

Gpri

a matrix with the initial values of the variance of gamma

Value

value

a number with the proposal for the gamma parameter

Details

Generate a proposal for the gamma parameter according to the model proposed by Cepeda(2001) and Cepeda and Gamerman(2005).

References

1.Cepeda C. E. (2001). Modelagem da variabilidade em modelos lineares generalizados. Unpublished Ph.D. tesis. Instituto de Matematicas. Universidade Federal do Rio do Janeiro. //http://www.docentes.unal.edu.co/ecepedac/docs/MODELAGEM0DAVARIABILIDADE.pdf http://www.bdigital.unal.edu.co/9394/. 2.Cepeda, E. C. and Gamerman D. (2005). Bayesian Methodology for modeling parameters in the two-parameter exponential family. Estadistica 57, 93 105.

Examples

library(betareg)
data(ReadingSkills)


Y <- as.matrix(ReadingSkills[,1])
n <- length(Y)
X1 <- as.matrix(ReadingSkills[,2])
for(i in 1:length(X1)){
  X1 <- replace(X1,X1=="yes",1)
  X1 <- replace(X1,X1=="no",0)
}
X0 <- rep(1, times=n)
X1 <- as.numeric(X1)
X2 <- as.matrix(ReadingSkills[,3])
X3 <- X1*X2
X <- cbind(X0,X1,X2,X3)
Z0 <-  X0 
Z <- cbind(X0,X1)
betas.ind=c(0,0,0,0)
gammas.ind=c(0,0)
gpri=c(0,0)
Gpri=diag(10,nrow=ncol(Z),ncol=ncol(Z))

gamma <- gammaproposal(Y,X,Z,betas.ind,gammas.ind,gpri,Gpri)
gamma