Score new samples using hat values

# S3 method for apd_hat_values
score(object, new_data, type = "numeric", ...)

Arguments

object

A apd_hat_values object.

new_data

A data frame or matrix of new predictors.

type

A single character. The type of predictions to generate. Valid options are:

  • "numeric" for a numeric value that summarizes the hat values for each sample across the training set.

...

Not used, but required for extensibility.

Value

A tibble of predictions. The number of rows in the tibble is guaranteed to be the same as the number of rows in new_data. For type = "numeric", the tibble contains two columns hat_values and hat_values_pctls. The column hat_values_pctls is in percent units so that a value of 11.5 indicates that, in the training set, 11.5 percent of the training set samples had smaller values than the sample being scored.

Examples

train_data <- mtcars[1:20,] test_data <- mtcars[21:32,] hat_values_model <- apd_hat_values(train_data) hat_values_scoring <- score(hat_values_model, new_data = test_data) hat_values_scoring
#> # A tibble: 12 x 2 #> hat_values hat_values_pctls #> <dbl> <dbl> #> 1 1.45 1 #> 2 0.852 90.0 #> 3 1.13 1 #> 4 1.19 1 #> 5 0.901 93.2 #> 6 0.335 6.34 #> 7 5.41 1 #> 8 5.91 1 #> 9 8.19 1 #> 10 5.11 1 #> 11 12.4 1 #> 12 0.960 1