binary_metrics: Fit metrics of observed and expected binary variables

In swash: Swash-Backwash Model for the Single Epidemic Wave

Fit metrics of observed and expected binary variables

Description

Calculation of fit metrices for binary variables (Sensitivity, specificity, accuracy)

Usage

binary_metrics(
  observed, 
  expected,
  no_information_rate = "negative"
  )

Arguments

observed	Numeric vector: Y observed
expected	Numeric vector: Y expected
no_information_rate	bool argument which indicates whether the no-information rate is calculated based on negatives or positives

Details

The function computes model performance metrices for binary outcomes. Observed and expected data must be stated by the user. The function returns sensitivity, specificity, accurracy, and no-information rate.

Value

list with two entries:

fit_metrics:	list with fit metrics (sens, spec, ...)
observed_expected:	data.frame with observed, expected and hit (1/0)

Author(s)

Thomas Wieland

References

Altman DG, Bland JM (1994) Diagnostic tests. 1: Sensitivity and specificity. British Medical Journal 308, 1552. \Sexpr[results=rd]{tools:::Rd_expr_doi("https://doi.org/10.1136/bmj.308.6943.1552")}.

Boehmke B, Greenwell B (2020) Hands-On Machine Learning with R (1 ed.). Taylor & Francis, New York, NY.

See Also

metrics, binary_metrics_glm

Examples

obs <- c(1,1,0,0,0,0,1,0,1)
exp <- c(0,1,0,0,0,0,1,0,0)

binary_metrics(
  obs,
  exp
)

swash documentation built on Feb. 15, 2026, 5:07 p.m.