scores_lnorm: Proper Scoring Rules for Log-Normal Forecasts

In HIDDA/forecasting: Forecasting Based on Surveillance Data

Proper Scoring Rules for Log-Normal Forecasts

Description

This is a simple wrapper around functions from the scoringRules package for predictions with a LN(meanlog, sdlog) distribution. The function is vectorized and preserves the dimension of the input.

Usage

scores_lnorm(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.