logs_nbmix: Simulation-Based Logarithmic Score Via 'dnbmix'

In HIDDA/forecasting: Forecasting Based on Surveillance Data

Simulation-Based Logarithmic Score Via dnbmix

Description

The function logs_nbmix computes the logarithmic score of forecasts based on mixtures of negative binomial (or Poisson) distributions via dnbmix(). This is different from the kernel density estimation approach available via scores_sample().

Usage

logs_nbmix(observed, means, size)

Arguments

observed	a vector of observed counts during the simulation period.
means	a n.ahead x n.sim matrix of means.
size	the dispersion parameter of the dnbinom() distribution or NULL (Poisson forecasts). Can also be time-varying (of length n.ahead).

Value

a vector of log-scores for the observed counts.

Author(s)

Sebastian Meyer

See Also

scores_sample() for an alternative approach of calculating the logarithmic score from simulation-based forecasts

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