data modeling - WinBUGS error: vector valued relation z must involve consecutive elements of variable -
i trying model multivariate probit model binary data. have been trying winbugs in return gives me error. ideas or suggestion warmly welcomed.
model{ (i in 1:ns){ ## loop on studies
for (k in 1:2){ ### loop on arm (j in 1:2){ ### loop on outcomes r[i,k,j] ~ dbin(p[i,k,j],n[i,k,j]); ## likelihood function p[i,k,j] <- phi(z[i,k,j]) z[i,k,1:2] ~ dmnorm(theta[i,1:2],with[i,,])i(-5, 5) #latent variable (z<0) or probit link theta[i,1] <- alpha[i,k,1] + beta[i,k,1] theta[i,2] <- alpha[i,k,2] + beta[i,k,2] } ###close loop on outcomes } ###close loop on arms alpha[i,2,1] <- 0 alpha[i,2,2] <- 0 alpha[i,1,1:2] ~ dnorm(0,.0001) beta[i,2,1:2] ~ dmnorm(d[1:2],prec[,]) beta[i,1,1] <- 0 beta[i,1,2] <- 0 ## priors on within study cov matrix with[i,1:2,1:2] <- inverse(cov.mat[i,1:2,1:2]) #define elements of within-study covariance matrix cov.mat[i,1,1] <- 1 cov.mat[i,2,2] <- 1 ### prior ipd data ###### cov.mat[i,1,2] ~ dbeta(a[i],b[i]) cov.mat[i,2,1] <- cov.mat[i,1,2] a[i]<-31.97 b[i]<- 4.52 }#### close loop on studies (i in 1:2) { d[i] ~ dnorm(0.0000e+00, 0.0001) # overall treatment effects } ## priors on between study cov matrix prec[1:2,1:2]<-inverse(tau[1:2,1:2]) pi<-3.14/2 a1~dunif(0, pi) rho.tau<-cos(a1) sd[1]~dunif(0,2) sd[2]~dunif(0,2) tau[1,1]<-pow(sd[1],2) tau[2,2]<-pow(sd[2],2) tau[2,1]<-tau[1,2] tau[1,2]<-sd[1]*sd[2]*rho.tau } #end model these data:
list(ns=2) t[,1,1] t[,1,2] t[,2,1] t[,2,2] r[,1,1] n[,1,1] r[,2,1] n[,2,1] r[,1,2] n[,1,2] r[,2,2] n[,2,2] 1 0 1 0 19 77 23 77 60 82 70 82 1 0 1 0 27 199 54 199 231 393 318 393 end the model syntactically correct , allows me load data. once compile error in title. thank given
it looks if inputting 2 2 matrix mean of multivariate normal distribution right here.
z[i,1:2,k] ~ dmnorm(theta[i,,],with[i,,])i(-5, 5) #latent variable (z<0) or probit link however, appears if z vector of length 2. need input vector mean of dmnorm , give associated variance covariance matrix (i.e. if supply vector of length 3, needs have 3 3 variance covariance matrix). right have 2 2 matrix input mean (4 parameters) , 2 2 variance covariance matrix. not know motivation behind model can't provide suggestions on how fix per se, seems me need index theta bit more in order prevent putting matrix dmnorm.
Comments
Post a Comment