Description Usage Arguments Details Value Author(s) References Examples
Propose a value for posterior distribution of the gamma parameter
1 | dpostg(X, Z, Y, betas, gammas, gpri, Gpri)
|
X |
object of class matrix, with the variables for modelling the mean |
Z |
object of class matrix, with the variables for modelling the variance |
Y |
object of class matrix, with the dependent variables |
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 beta |
Gpri |
a matrix with the initial values of the variance of beta |
Generate a proposal for the beta parameter according to the model proposed by Cepeda(2001) and Cepeda and Gamerman(2005).
value |
a matrix with the proposal for beta |
Daniel Jaimes dajaimesc@unal.edu.co, Margarita Marin mmarinj@unal.edu.co, Javier Rojas jarojasag@unal.edu.co, Hugo Andres Gutierrez Rojas hugogutierrez@usantotomas.edu.co, Martha Corrales martha.corrales@usa.edu.co, Maria Fernanda Zarate mfzaratej@unal.edu.co, Ricardo Duplat rrduplatd@unal.edu.co, Luis Villaraga lfvillarragap@unal.edu.co, Edilberto Cepeda-Cuervo ecepedac@unal.edu.co
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 Unpublished Ph.D. tesis.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/MODELAGEMDAVARIABILIDADE.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.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 | 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)
bpri=c(0,0)
Bpri=diag(10,nrow=ncol(Z),ncol=ncol(Z))
gamma <- dpostg(X,Z,Y,betas.ind,gammas.ind,bpri,Bpri)
gamma
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