measures (version 0.2)

SSR: Spherical Scoring Rule

Description

Defined as: mean(p_i(sum_j(p_ij))), where p_i is the predicted probability of the true class of observation i and p_ij is the predicted probablity of observation i for class j. See: Bickel, J. E. (2007). Some comparisons among quadratic, spherical, and logarithmic scoring rules. Decision Analysis, 4(2), 49-65.

Usage

SSR(probabilities, truth)

Arguments

probabilities

[numeric] vector (or matrix with column names of the classes) of predicted probabilities

truth

vector of true values

Examples

# NOT RUN {
n = 20
set.seed(122)
truth = as.factor(sample(c(1,2,3), n, replace = TRUE))
probabilities = matrix(runif(60), 20, 3)
probabilities = probabilities/rowSums(probabilities)
colnames(probabilities) = c(1,2,3)
SSR(probabilities, truth)
# }