Nothing
`confint.brglm` <-
function (object, parm = 1:length(coef(object)), level = 0.95,
verbose = TRUE, endpoint.tolerance = 0.001, max.zoom = 100,
zero.bound = 1e-08, stepsize = 0.5, stdn = 5, gridsize = 10,
scale = FALSE, method = "smooth", ci.method = "union",
n.interpolations = 100, ...)
{
prof <- profile.brglm(object, gridsize = 10, stdn = stdn, stepsize = stepsize,
grid.bounds = NULL, level = level, which = parm, verbose = verbose,
zero.bound = zero.bound, scale = scale)
ci <- confint.profile.brglm(prof, method = method, ci.method = ci.method,
endpoint.tolerance = endpoint.tolerance, max.zoom = max.zoom,
n.interpolations = n.interpolations, verbose = verbose)
drop(ci)
}
`confint.profile.brglm` <-
function (object, parm, level = 0.95, method = "smooth", ci.method = "union",
endpoint.tolerance = 0.001, max.zoom = 100, n.interpolations = 100,
verbose = TRUE, ...)
{
alpha <- 1 - attr(object, "level")
if (!(ci.method %in% c("union", "mean")))
stop("Invalid 'ci.method'.")
if (is.null(object$profilesBR)) {
ci <- profConfint(object$profilesML, method = method,
endpoint.tolerance = endpoint.tolerance, max.zoom = max.zoom,
n.interpolations = n.interpolations, verbose = FALSE)
}
else {
if (verbose)
cat("Calculating confidence intervals for the ML fit using deviance profiles...\n")
ci1 <- profConfint(object$profilesML, method = method,
endpoint.tolerance = endpoint.tolerance, max.zoom = max.zoom,
n.interpolations = n.interpolations, verbose = FALSE)
fit <- object$profilesBR$fit
if (verbose) {
if (fit$pl | all(fit$family$link == "logit"))
cat("Calculating confidence intervals for the BR fit using penalized likelihood profiles...\n")
else cat("Calculating confidence intervals for the BR fit using modified score statistic profiles...\n")
}
ci2 <- profConfint(object$profilesBR, method = method,
endpoint.tolerance = endpoint.tolerance, max.zoom = max.zoom,
n.interpolations = n.interpolations, verbose = FALSE)
ci <- switch(ci.method, union = cbind(pmin(ci1[, 1],
ci2[, 1]), pmax(ci1[, 2], ci2[, 2])), mean = (ci1 +
ci2)/2)
}
profNames <- names(object$profilesML$profiles)
dimnames(ci) <- list(profNames, paste(c(alpha/2, 1 - alpha/2) *
100, "%"))
attr(ci, "profileModel object") <- NULL
ci
}
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