Nothing
cost2_gaussian <- function(x, data_x, data_y, prior_st)
{
dm = ncol(data_x)
data_num = nrow(data_x)
tau2 = h = vector(,dm)
hn = data_num^(-1/(4+dm))
for(k in 1:dm)
{
tau2[k] = exp(x[k])
h[k] = sqrt(tau2[k]) * hn
}
hprod = prod(h)
cont = exp(-0.5 * dm * log(2.0 * pi))
cv_int = vector(,data_num)
for(i in 1:data_num)
{
temp = (sweep(data_x[-i,], 2, data_x[i,])/h)^2
weight = cont * exp(-0.5 * apply(temp,1,sum))/hprod
suma = sum(weight * data_y[-i])
sumb = sum(weight)
cv_int[i] = (data_y[i] - suma/sumb)^2
}
cv = sum(cv_int) + prior_st
return(0.5*cv)
}
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