Statistical Score
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A Statistical Score is a summary statistic value that is a score (for some statistical score function).
- See: Probability Value, Confidence Interval, Likelihood Value, Parametric Model, Gradient, Statistical Inference, Test Statistic, Maximum Likelihood, Cramér–Rao Bound.
References
2017
- (Wikipedia, 2017) ⇒ https://en.wikipedia.org/wiki/Score_(statistics) Retrieved:2017-12-3.
- In statistics, the score, score function, efficient scoreor informant indicates how sensitive a likelihood function [math]\displaystyle{ \mathcal L(\theta; X) }[/math] is to its parameter [math]\displaystyle{ \theta }[/math] . Explicitly, the score for [math]\displaystyle{ \theta }[/math] is the gradient of the log-likelihood with respect to [math]\displaystyle{ \theta }[/math] .
The score plays an important role in several aspects of inference. For example:
:*in formulating a test statistic for a locally most powerful test;:*in approximating the error in a maximum likelihood estimate;:*in demonstrating the asymptotic sufficiency of a maximum likelihood estimate;:*in the formulation of confidence intervals;:*in demonstrations of the Cramér–Rao inequality. The score function also plays an important role in computational statistics, as it can play a part in the computation of
maximum likelihood estimates.
- In statistics, the score, score function, efficient scoreor informant indicates how sensitive a likelihood function [math]\displaystyle{ \mathcal L(\theta; X) }[/math] is to its parameter [math]\displaystyle{ \theta }[/math] . Explicitly, the score for [math]\displaystyle{ \theta }[/math] is the gradient of the log-likelihood with respect to [math]\displaystyle{ \theta }[/math] .