Nothing
prior.SIGMA<-function(data,f1,f2,time.course){
n<-dim(data)[1]/time.course
n1<-nlevels(as.factor(f1))
if (length(f2)>1){
n2<-nlevels(as.factor(f2))
dg<-length(f1)-n1*n2
}
if (length(f2)==1){
dg<-length(f1)-n1
}
s<-matrix(nrow=time.course,ncol=n)
z<-matrix(0,nrow=time.course,ncol=time.course)
for (i in 1:n){
ix<-c(((i-1)*time.course+1):(i*time.course))
temp<-sigma.hat(data[ix,],f1,f2)
s[,i]<-diag(temp)
z<-z+temp
}
v<-vector(length=time.course)
for (i in 1:time.course){
sg<-s[i,]
zg<-log(sg)
eg<-zg-digamma(dg/2)+log(dg/2)
e<-mean(eg)
x<-mean((eg-e)^2*n/(n-1)-trigamma(dg/2))
if (x<=0){
v[i]<-10^5
}
else{
v[i]<-2*trigammaInverse(x)
}
}
v0<-max(mean(v),time.course+6)
LAMBDA<-1/v0*(v0-time.course-1)*z/(n-1)
v0<-mean(v)
return(list(LAMBDA=LAMBDA,v0=v0,df=dg))
}
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