Score (statistics) - Definition

Definition

The score or efficient score is the gradient (the vector of partial derivatives), with respect to some parameter, of the logarithm (commonly the natural logarithm) of the likelihood function. If the observation is and its likelihood is, then the score can be found through the chain rule:


V
=
\frac{\partial}{\partial\theta} \log L(\theta;X)
=
\frac{1}{L(\theta;X)} \frac{\partial L(\theta;X)}{\partial\theta}.

Thus the score indicates the sensitivity of (its derivative normalized by its value). Note that is a function of and the observation, so that, in general, it is not a statistic. However in certain applications, such as the score test, the score is evaluated at a specific value of (such as a null-hypothesis value, or at the maximum likelihood estimate of ), in which case the result is a statistic.

Read more about this topic:  Score (statistics)

Famous quotes containing the word definition:

    “I’m beginning to think that the proper definition of “Man” is “an animal that writes letters.””
    —Lewis Carroll [Charles Lutwidge Dodgson] (1832–1898)

    “The definition of good prose is proper words in their proper places; of good verse, the most proper words in their proper places. The propriety is in either case relative. The words in prose ought to express the intended meaning, and no more; if they attract attention to themselves, it is, in general, a fault.”
    —Samuel Taylor Coleridge (1772–1834)

    “The very definition of the real becomes: that of which it is possible to give an equivalent reproduction.... The real is not only what can be reproduced, but that which is always already reproduced. The hyperreal.”
    —Jean Baudrillard (b. 1929)