scores_moments {scoringRules} | R Documentation |
Scoring Rules for a Vector of Moments
Description
Calculate scores (DSS, ESS) given observations and moments of the predictive distributions.
Usage
dss_moments(y, mean = 0, var = 1)
ess_moments(y, mean = 0, var = 1, skew = 0)
Arguments
y |
vector of realized values. |
mean |
vector of mean values. |
var |
vector of variance values. |
skew |
vector of skewness values. |
Details
The skewness of a random variable X
is the third standardized moment
E[(\frac{X-\textnormal{mean}}{\sqrt{\textnormal{var}}})^3].
Value
Value of the score. A lower score indicates a better forecast.
Author(s)
Alexander Jordan, Sebastian Lerch
References
Dawid-Sebastiani score:
Dawid, A.P. and P. Sebastiani (1999): 'Coherent dispersion criteria for optimal experimental design' The Annals of Statistics, 27, 65-81. doi:10.1214/aos/1018031101
Error-spread score:
Christensen, H.M., I.M. Moroz, and T.N. Palmer (2015): 'Evaluation of ensemble forecast uncertainty using a new proper score: Application to medium-range and seasonal forecasts', Quarterly Journal of the Royal Meteorological Society, 141, 538-549. doi:10.1002/qj.2375