x=5
pi=3.14159
model {for (i in 1:M) {
for (j in 1:MM) { 
yMin[i] ~ dnorm( meanyMin , precyMin )
yMax[i] ~ dnorm( meanyMax , precyMax )
            tmp1[i] <- meantMid + be4Mid * e4pos[i]
tMid[i] ~ dnorm( tmp1[i] , prectMid )
            tmp2[i] <- meanRate + be4Rate * e4pos[i]
            Rate[i] ~ dnorm( tmp2[i] , precRate )
}}
for(k in 1:5) {
for (j in 1:NN ) {
      mu[j] <- yMin[subj[j]] + 
( yMax[subj[j]] - yMin[subj[j]] ) /
 ( 1 + exp( ( X[j] - tMid[subj[j]] ) / Rate[subj[j]] ) )
Y[j] ~ dnorm( mu[j] , precY )I(0,100)
} }
      
be4Mid ~ dnorm( meanbe4Mid , precbe4Mid )
be4Rate ~ dnorm( meanbe4Rate , precbe4Rate )

precY <- pow( sdY ,-2)
sdY ~ dunif(0,20)

meanyMin ~ dunif(0.01, 80);meanyMax ~ dunif(20, 99.99);meantMid ~ dnorm(70, 0.001)
meanRate ~ dunif(-20, 100)

meanbe4Mid ~ dnorm(0, 50)
meanbe4Rate ~ dnorm(0, 15)


precyMin <- pow( sdyMin ,-2)
sdyMin ~ dunif(0,40)
precyMax <- pow( sdyMax ,-2)
sdyMax ~ dunif(0,30)
prectMid <- pow( sdtMid ,-2)
sdtMid ~ dunif(0,30)
precRate <- pow( sdRate ,-2)
sdRate ~ dunif(0,20)

precbe4Mid <- pow( sdbe4Mid ,-2)
sdbe4Mid ~ dunif(0,30)
precbe4Rate <- pow( sdbe4Rate ,-2)
sdbe4Rate ~ dunif(0,10)
}

data[]=c(1,2,4)