scores#

Scoring rules for point estimation.

Classes

MeanScore(**kwargs)	$S(\hat{\theta },\theta )=|\hat{\theta }-\theta {|}^2$
MedianScore(**kwargs)	$S(\hat{\theta },\theta )=|\hat{\theta }-\theta |$
MultivariateNormalScore([dim, links])	$S({\hat{p}}_{\mu ,\mathrm{\Sigma }},\theta ;k)=-\log (\mathcal{N}(\theta ;\mu ,\mathrm{\Sigma }))$
NormedDifferenceScore(k, **kwargs)	$S(\hat{\theta },\theta ;k)=|\hat{\theta }-\theta {|}^k$
ParametricDistributionScore(**kwargs)	$S({\hat{p}}_{\varphi },\theta ;k)=-\log ({\hat{p}}_{\varphi }(\theta ))$
QuantileScore([q, links])	$S({\hat{\theta }}_i,\theta ;{\tau }_i)=({\hat{\theta }}_i-\theta )({\mathbf{1}}_{\hat{\theta }-\theta >0}-{\tau }_i)$
ScoringRule([subnets, subnets_kwargs, links])	Base class for scoring rules.