model
{
#omega ~ dnorm( 0.0,1.0E-6)I(0,100)
  # alpha ~ dnorm( 0.0,1.0E-6)I(0,1)
   #beta ~ dnorm( 0.0,1.0E-6)I(0,1)
a1~dnorm( 0.0,1.0E-6)I(0,1)
a2~dnorm( 0.0,1.0E-6)I(0,1)
b1~dnorm( 0.0,1.0E-6)I(0,1)
b2~dnorm( 0.0,1.0E-6)I(0,1)
alpha0~dnorm( 0.0,1.0E-6)I(0,100)
alpha1~dnorm( 0.0,1.0E-6)I(0,1)
beta1~ dnorm( 0.0,1.0E-6)I(0,1)
tau.a~dgamma(0.001,0.001)
sigma[1]<-alpha0
for(t in 2:n){
sigma[t]<-alpha0+alpha1*kis[t-1]*kis[t-1]+beta1*sigma[t-1]
}
for(t in 1:n){
tau[t]<-1/sigma[t]
y[t]~dnorm(mu[t],tau[t])
kis[t]<-y[t]-mu[t]
u[t]~dnorm(0,tau.a)
}
mu[1]<-0
mu[2]<-0
for(t in 3:n){
mu[t]<-a1*y[t-1]+a2*y[t-2]+u[t]+b1*u[t-1]+b2*u[t-2]
}
}
list(y = c(0.62933, 0.95565, 0.29702, 0.29889, -0.48426, 0.27024, 0.13400, 0.52710,
0.63116, -0.27419), n = 10 )
list(alpha0 = 0, alpha1 = 0, beta1 = 0)
list(alpha0=0,alpha1=0,beta1=0,a1=0,a2=0,b1=0,b2=0,tau.a=1)
DATA
list(n=10,y=c(2.64 ,3.34 ,3.94 ,3.74 ,3.84 ,3.84 ,3.94 ,3.74 ,3.24 ,2.84))