Nothing
summary.BinaryEPPM <-
function(object, ...) {
nobs <- nrow(object$covariates.matrix.p)
p.par <- rep(0,nobs)
scalef.par <- rep(1,nobs)
vone <- rep(1,nobs)
scalef.limit <- rep(0,nobs)
npar <- length(object$optim$par)
# Calculation of p and means from parameter estimates and design matrices
lp.p <- object$covariates.matrix.p%*%object$coefficients$p.est +
object$offset.p
# inverse of link function
p.par <- attr(object$link, which="p")$linkinv(lp.p)
if (object$model.type=="p only") {
wk.object <- object
if (object$model.name=="generalized binomial") {
# Changing to test of b=1 for the generalized binomial
# error in version 2.0 corrected in version 2.1
wk.object$coefficients$scalef.est <-
wk.object$coefficients$scalef.est - 1 } # end of generalized binomial
coeff.table.p <- coeftest(wk.object)
coeff.table.scalef <- NULL
} else {
wk.object <- object
wk.object$coefficients <- object$coefficients[1]
wk.object$vcov <- vcov(object,model="p")
coeff.table.p <- coeftest(wk.object)
wk.object <- object
wk.object$coefficients <- object$coefficients[2]
wk.object$vcov <- vcov(object,model="scale.factor")
coeff.table.scalef <- coeftest(wk.object)
} # end if (model.type=="p only")
object <- list(data.type=object$data.type, call=object$call, formula=object$formula,
model.type=object$model.type, model.name=object$model.name,
link=object$link, offset.p=object$offset.p,offset.scalef=object$offset.scalef,
coeff.table.p=coeff.table.p, coeff.table.scalef=coeff.table.scalef, loglik=object$loglik,
n=object$nobs, nobs=object$nobs, df.null=object$df.null, df.residual=object$df.residual,
vnmax=object$vnmax, weights=object$weights, converged=object$converged,
method=object$method,pseudo.r.squared=object$pseudo.r.squared,
optim=object$optim,control=object$control, fitted.values=object$fitted.values,
y=object$y, terms=object$terms, npar=npar)
class(object) <- "summaryBinaryEPPM"
object }
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