On Wed, 2003-01-15 at 09:18, Douglas Bates wrote: > "Matthew L. Fidler" <[EMAIL PROTECTED]> writes: > > ... > > > logLik(short.alif.fit); > > `log Lik.' 6.307024 (df=1) > > > > My problem with this number is that exp(logLik) > 1. If the error > > structure is independent, identically distributed normal (which I > > assumed was the case), then the Likelihood function should only give a > > number from 0 to 1... > > Why? The likelihood is the product of the probability densities of > the observations given the parameters and a probability density can be > greater than 1. > > The belief that a likelihood must be less than 1 is a common > misconception
True, if the variance is small (less than one), it can have that
feature. I forgot; thank you for reminding me. However I still cannot
get the non-central F to return the right tail (according to my linear
model's noncentral F distribution tables....) I thought it wasn't
working because I couldn't get it to produce the log-liklihood function
that I derived. I forgot to divide the residual sum of squares by N,
however.... sorry.
--
Matthew L. Fidler
[EMAIL PROTECTED]
421 Wakra Way, Suite 318
Salt Lake City, UT 84108
(801) 581-7125
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Accident, n.:
A condition in which presence of mind is good, but absence of
body is better.
-- Foolish Dictionary
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