Brier score (brier)

Computes the Brier score for binary outcomes as squared error between the observed label and predicted event probability.

Usage

measure_brier(y, ypred, log_weights = NULL, pointwise = NULL)

Arguments

y

A numeric vector of binary outcomes coded as 0 or 1.

ypred

A numeric matrix of posterior predictive probabilities with dimensions draws x observations.

log_weights

Optional numeric matrix of unnormalized log-importance weights with dimensions \(S \times n\). Weights are column-normalized before computing each per-observation contribution.

pointwise

Optional numeric vector of precomputed pointwise Brier scores. If provided, y, ypred, and log_weights are ignored.

Value

An object of class "measure": a list with:

estimates

A 1 \(\times\) 2 matrix. The row is named after the measure, the columns are Estimate and SE (standard error).

pointwise

An \(n \times 1\) matrix of per-observation values. The column is named after the measure.

extra

Optional. Auxiliary data for the standard error of a difference. Most measures do not set it.

Attributes measure (i.e., measure name) and dims (draws \(\times\) observations) are also set. Use print() for a readable summary.

Examples

y <- c(1, 0, 1)
ypred <- matrix(c(0.8, 0.2, 0.7, 0.9, 0.4, 0.6), nrow = 2)
measure_brier(y, ypred)
#> 
#> Computed from 2 draws by 3 observations.
#> 
#>       Estimate    SE
#> brier    0.380 0.130