#' @export
get_predictions.rq <- function(model,
data_grid = NULL,
terms = NULL,
ci_level = 0.95,
type = NULL,
typical = NULL,
vcov = NULL,
vcov_args = NULL,
condition = NULL,
interval = "confidence",
bias_correction = FALSE,
link_inverse = insight::link_inverse(model),
model_info = NULL,
verbose = TRUE,
...) {
if (!is.null(ci_level) && !is.na(ci_level)) {
ci <- "confidence"
} else {
ci <- "none"
}
prdat <- stats::predict(
model,
newdata = data_grid,
interval = ci,
level = ci_level,
...
)
# get predicted values, on link-scale
data_grid$predicted <- prdat[, 1]
if (ci == "none") {
data_grid$conf.low <- NA
data_grid$conf.high <- NA
} else {
data_grid$conf.low <- prdat[, 2]
data_grid$conf.high <- prdat[, 3]
}
data_grid
}
#' @export
get_predictions.rqss <- get_predictions.rq
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