No L(H|D) is not a probability and it does not
obey the laws of probability.
Your citation references a discussion about
something else, fiducial probability I would
think.
The likelihood ratio is a fundamental part of
Neyman-Pearson. It is the heart of their
fundamental theorem.
The fit of distributions to data does not seem to
have anything to do with the question that was
asked. Perhaps you can elaborate.
>
> "The Mathematical Likelihood assignable to every value of the unknown
> parameter p supplies a zoning of the admissible range of values more
> appropriate to the observations than by the system of cofidence belts....It
> is, like Mathematical Probability, a well-defined quantitative feature of
> the logical situations....but it is a quantity of a different kind from
> probability, and does not obey the laws of probability". (page 72)
>
> Therefore L(H|D) which is a probability, obeying probability laws, differs
> from Fisher's concept.
>
> A good many years ago I used the L(H|D) idea to determine the probability of
> obtaining a given set of data from a two parameter distribution (the
> negative binomial) for different values of the parameters. Although I got a
> significant increase in probability with the negative binomial in comparison
> to the Poisson, I could not sell the idea. The concept of a two parameter
> non-Weibull failure rate distribution was totally not believable.
> ............................................................................
> .........
>
--
Bob Wheeler --- (Reply to: [EMAIL PROTECTED])
ECHIP, Inc.
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