If is one-dimensional, then the score function is simply referred to as the score of .
The maximum likelihood estimate (MLE) of the parameter vector can usually be found by finding the solutions of the likelihood equations. The likelihood equations may also be formed by setting the gradient of the plain likelihood function to zero. The use of the log function often facilitates the algebra as many distributions are exponential in nature. For some distributions it may also be necessary to test that the solution to the likelihood equations is really a minimum as opposed to a point of inflection.
and so the score function is
where . To find the MLE of , we set and solve for . So the MLE of .
|Date of creation||2013-03-22 14:28:02|
|Last modified on||2013-03-22 14:28:02|
|Last modified by||CWoo (3771)|