scores_lnorm_discrete: Proper Scoring Rules for _Discretized_ Log-Normal Forecasts

In HIDDA/forecasting: Forecasting Based on Surveillance Data

Proper Scoring Rules for Discretized Log-Normal Forecasts

Description

Compute scores for discretized log-normal forecasts. The function is vectorized and preserves the dimension of the input.

Usage

scores_lnorm_discrete(x, meanlog, sdlog, which = c("dss", "logs"))

Arguments

x	the observed counts.
meanlog, sdlog	parameters of the log-normal distribution, i.e., mean and standard deviation of the distribution on the log scale.
which	a character vector specifying which scoring rules to apply. The Dawid-Sebastiani score ("dss") and the logarithmic score ("logs") are available and both computed by default.

Value

scores for the predictions of the observations in x (maintaining their dimensions).

HIDDA/forecasting documentation built on Jan. 11, 2024, 1:11 a.m.