Nothing
`modifiedScoreStatistic` <-
function (fm, X, dispersion = 1)
{
y <- fm$y
wt <- fm$prior
LP <- fm$linear
family <- fm$family
probs <- family$linkinv(LP)
dmu.deta <- family$mu.eta
variance <- family$variance
we <- c(wt * dmu.deta(LP)^2/variance(probs))
W.X <- sqrt(we) * X
XWXinv <- chol2inv(chol(crossprod(W.X)))
hats <- diag(X %*% XWXinv %*% t(we * X))
cur.model <- modifications(family, pl = fm$pl)(probs)
mod.wt <- wt + c(hats * cur.model$at)
y.adj <- (y * wt + hats * cur.model$ar)/mod.wt
s.star <- t(c(dmu.deta(LP)/variance(probs)) * X) %*% ((y.adj -
probs) * mod.wt)
t(s.star) %*% XWXinv %*% s.star
}
`penalizedDeviance` <-
function (fm, X, dispersion = 1)
{
Y <- fm$y
LP <- fm$linear.predictor
fam <- fm$family
wt <- fm$prior.weights
mu <- fm$fitted.values
we <- fm$weights
W.X <- sqrt(we) * X
(sum(fam$dev.resid(Y, mu, wt)) - log(det(crossprod(W.X))))/dispersion
}
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