0
votes

I am trying to fit the model below using rjags but I get a dimension mismatch error. The model runs well in WinBUGS and I can't figure out how to change the code. Thanks in advance for any help.

Data:

dataset <- list(n1 = 462, n2 = 537,
                y1 = structure(.Data = c(37, 55, 7, 363), .Dim = c(2, 2)),
                y2 = structure(.Data = c(104, 26, 22, 385), .Dim = c(2, 2)),
                Q = 2)

Initial values for chains

inits <- list(pi1 = 0.1, pi2 = 0.3, SeMAT = 0.80, SpMAT = 0.90,
              SeCMB = 0.90, SpCMB = 0.9995)

Model

model <- 
'model {
    y1[1:Q, 1:Q] ~ dmulti(p1[1:Q, 1:Q], n1)
    y2[1:Q, 1:Q] ~ dmulti(p2[1:Q, 1:Q], n2)
    p1[1, 1] <- pi1 * SeMAT * SeCMB + (1 - pi1) * (1 - SpMAT) * (1 - SpCMB)
    p1[1, 2] <- pi1 * SeMAT * (1 - SeCMB) + (1 - pi1) * (1 - SpMAT) * SpCMB
    p1[2, 1] <- pi1 * (1 - SeMAT) * SeCMB + (1 - pi1) * SpMAT * (1 - SpCMB)
    p1[2, 2] <- pi1 * (1 - SeMAT) * (1 - SeCMB) + (1 - pi1) * SpMAT * SpCMB
    p2[1, 1] <- pi2 * SeMAT * SeCMB + (1 - pi2) * (1 - SpMAT) * (1 - SpCMB)
    p2[1, 2] <- pi2 * SeMAT * (1 - SeCMB) + (1 - pi2) * (1 - SpMAT) * SpCMB
    p2[2, 1] <- pi2 * (1 - SeMAT) * SeCMB + (1 - pi2) * SpMAT * (1 - SpCMB)
    p2[2, 2] <- pi2 * (1 - SeMAT) * (1 - SeCMB) + (1 - pi2) * SpMAT * SpCMB
    SeMAT ~ dbeta(1, 1) 
    SpMAT ~ dbeta(1, 1) 
    SeCMB ~ dbeta(1, 1)
    SpCMB ~ dbeta(1, 1)
    pi1~ dbeta(1, 1)
    pi2 ~ dbeta(1, 1) 
}'

writeLines(model, 'model.txt')

jags.mod <- jags.model(file = 'model.txt',
                   data = dataset,
                   inits = inits, 
                   n.chains = 3)

Error

Error in jags.model(file = "model.txt", data = dataset, inits = inits, : RUNTIME ERROR: Cannot insert node into y1[1:2,1:2]. Dimension mismatch

1

1 Answers

0
votes

Did you mean to specify a multivariate distribution, not a multinomial one?

The multinomial distribution, dmulti, takes two parameters:n, an integer as you've specified it, and pi a single dimensional vector that sums to one.

Your p1 and p2 are both multi-dimensional, but can't be with that distribution.