Score new samples using hat values
# S3 method for apd_hat_values score(object, new_data, type = "numeric", ...)
object  A 

new_data  A data frame or matrix of new predictors. 
type  A single character. The type of predictions to generate. Valid options are:

...  Not used, but required for extensibility. 
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.
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