Balakrishnan, 1994, On the Compound Generalized
Poisson Distributions, Astin Bulletin, 24: 255-263.
(In the
Poisson distribution tables, m is the mean value for the given grouping.)
For the
Poisson distribution the interest is in a random variable, X, that represents the number of occurrences of an event within a fixed time.
The truncated
Poisson distribution on the given range [0, [n.sub.i]] is obtained by normalising the
Poisson distribution, as follows:
gamma or
Poisson distribution, with a choice of three link functions:
Whenever the assumption of
Poisson distribution does not hold, statisticians tend to adopt alternative models to strengthen the quality control process.
57-60) addressed a problem that recurs in studies of spatial distributions of plants: How to calculate a random expected distribution, in the manner of a
Poisson distribution, when the plants are large and take up nonnegligible fractions of the quadrats employed in their study.
Sampling from the
poisson distribution on a computer, Computing 17, 1976, 147-156.
In this article, we assume that the number of accidents is based on a
Poisson distribution but that the number of claims is generated by censorship of this
Poisson distribution.
The model structure can be based on a normal, gamma or
Poisson distribution, with a choice of three link functions: the identity, logarithm and reciprocal link functions.
In this section predictive distributions for the exponential and
Poisson distributions are provided.
Nonparametric Tests for Mixed
Poisson Distributions, by Jacques Carriere (The University of Manitoba, Winnipeg, Canada)
