Nothing
impsampling=function (logf, tpar, h, n, data)
{
theta = rmt(n, mean = c(tpar$m), S = tpar$var, df = tpar$df)
lf=matrix(0,c(dim(theta)[1],1))
for (j in 1:dim(theta)[1]) lf[j]=logf(theta[j,],data)
H=lf
for (j in 1:dim(theta)[1]) H[j]=h(theta[j,])
lp = dmt(theta, mean = c(tpar$m), S = tpar$var, df = tpar$df,
log = TRUE)
md = max(lf - lp)
wt = exp(lf - lp - md)
est = sum(wt * H)/sum(wt)
SEest = sqrt(sum((H - est)^2 * wt^2))/sum(wt)
return(list(est = est, se = SEest, theta = theta, wt = wt))
}
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