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Calculate partial area under curve

pauc.Rd

Calculates area under curve curve in an specific TPR or FPR region.

Usage

pauc(
  data = NULL,
  response,
  predictor,
  ratio,
  lower_threshold,
  upper_threshold,
  .condition = NULL
)

Arguments

data

A data.frame or extension (e.g. a tibble) containing values for predictors and response variables.

response

A data variable which must be a factor, integer or character vector representing the prediction outcome on each observation (Gold Standard).

If the variable presents more than two possible outcomes, classes or categories:

  • The outcome of interest (the one to be predicted) will remain distinct.

  • All other categories will be combined into a single category.

New combined category represents the "absence" of the condition to predict. See .condition for more information.

predictor

A data variable which must be numeric, representing values of a classifier or predictor for each observation.

ratio

Ratio or axis where to apply calculations.

  • If "tpr", only points within the specified region of TPR, y axis, will be considered for calculations.

  • If "fpr", only points within the specified region of FPR, x axis, will be considered for calculations.

lower_threshold, upper_threshold

Two numbers between 0 and 1, inclusive. These numbers represent lower and upper bounds of the region where to apply calculations.

.condition

A value from response that represents class, category or condition of interest which wants to be predicted.

If NULL, condition of interest will be selected automatically depending on response type.

Once the class of interest is selected, rest of them will be collapsed in a common category, representing the "absence" of the condition to be predicted.

See vignette("selecting-condition") for further information on how automatic selection is performed and details on selecting the condition of interest.

Value

A numeric value representing the area under ROC curve in the specified region.

Examples

# Calculate pauc of Sepal.Width as a classifier of setosa species in
# in TPR = (0.9, 1)
pauc(
  iris,
  response = Species,
  predictor = Sepal.Width,
  ratio = "tpr",
  lower_threshold = 0.9,
  upper_threshold = 1
)
#> ℹ Upper threshold 1 already included in points.
#> • Skipping upper threshold interpolation
#> [1] 0.0472
# Calculate pauc of Sepal.Width as a classifier of setosa species in
# in FPR = (0, 0.1)
pauc(
  iris,
  response = Species,
  predictor = Sepal.Width,
  ratio = "fpr",
  lower_threshold = 0,
  upper_threshold = 0.1
)
#> ℹ Lower 0 and upper 0.1 thresholds already included in points
#> • Skipping lower and upper threshold interpolation
#> [1] 0.0476