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Fixes #1212 enabled augment() for quartile regression #1292

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Sep 19, 2025
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Fixes #1212 enabled augment() for quartile regression #1292

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51 changes: 45 additions & 6 deletions R/augment.R
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Original file line number Diff line number Diff line change
Expand Up @@ -31,6 +31,12 @@
#' page in the references below). This enables the user to compute performance
#' metrics in the \pkg{yardstick} package.
#'
#' ## Quantile Regression
#'
#' For quantile regression models, a `.pred_quantile` column is added that
#' contains the quantile predictions for each row. This column has a special
#' class `"quantile_pred"` and can be unnested using [tidyr::unnest()]
#'
#' @param new_data A data frame or matrix.
#' @param ... Not currently used.
#' @rdname augment
Expand Down Expand Up @@ -78,14 +84,31 @@
#' augment(cls_xy, cls_tst)
#' augment(cls_xy, cls_tst[, -3])
#'
#' # ------------------------------------------------------------------------------
#'
#' # Quantile regression example
#' qr_form <-
#' linear_reg() |>
#' set_engine("quantreg") |>
#' set_mode("quantile regression", quantile_levels = c(0.25, 0.5, 0.75)) |>
#' fit(mpg ~ ., data = car_trn)
#'
#' augment(qr_form, car_tst)
#' augment(qr_form, car_tst[, -1])
#'
augment.model_fit <- function(x, new_data, eval_time = NULL, ...) {
new_data <- tibble::new_tibble(new_data)
res <-
switch(
x$spec$mode,
"regression" = augment_regression(x, new_data),
"classification" = augment_classification(x, new_data),
"censored regression" = augment_censored(x, new_data, eval_time = eval_time),
"regression" = augment_regression(x, new_data),
"classification" = augment_classification(x, new_data),
"censored regression" = augment_censored(
x,
new_data,
eval_time = eval_time
),
"quantile regression" = augment_quantile_regression(x, new_data),
cli::cli_abort(
c(
"Unknown mode {.val {x$spec$mode}}.",
Expand All @@ -106,7 +129,11 @@ augment_regression <- function(x, new_data) {
ret <- dplyr::mutate(ret, .resid = !!rlang::sym(y_nm) - .pred)
}
}
dplyr::relocate(ret, dplyr::starts_with(".pred"), dplyr::starts_with(".resid"))
dplyr::relocate(
ret,
dplyr::starts_with(".pred"),
dplyr::starts_with(".resid")
)
}

augment_classification <- function(x, new_data) {
Expand All @@ -117,11 +144,15 @@ augment_classification <- function(x, new_data) {
}

if (spec_has_pred_type(x, "class")) {
ret <- dplyr::bind_cols(predict(x, new_data = new_data, type = "class"), ret)
ret <- dplyr::bind_cols(
predict(x, new_data = new_data, type = "class"),
ret
)
}
ret
}


# nocov start
# tested in tidymodels/extratests#
augment_censored <- function(x, new_data, eval_time = NULL) {
Expand All @@ -145,7 +176,8 @@ augment_censored <- function(x, new_data, eval_time = NULL) {
.filter_eval_time(eval_time)
ret <- dplyr::bind_cols(
predict(x, new_data = new_data, type = "survival", eval_time = eval_time),
ret)
ret
)
# Add inverse probability weights when the outcome is present in new_data
y_col <- .find_surv_col(new_data, fail = FALSE)
if (length(y_col) != 0) {
Expand All @@ -155,3 +187,10 @@ augment_censored <- function(x, new_data, eval_time = NULL) {
ret
}
# nocov end

augment_quantile_regression <- function(x, new_data) {
ret <- new_data
check_spec_pred_type(x, "quantile")
ret <- dplyr::bind_cols(predict(x, new_data = new_data), ret)
dplyr::relocate(ret, dplyr::starts_with(".pred"))
}
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