Univeristy of Alabama in Huntsville


IDL Routines from Phillip Bitzer and UAH Lightning Group

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Stats, Poisson, ATS606

This routine returns the Poisson probability distribution function for a given value(s) and mean. Of course, the Poisson distribution is given by: $$ P(n) = \frac{1}{n\!}\lambda^n e^{-\lambda} $$

You can provide a scalar or an array of values for $n$.

WARNING: Very little error checking has been implemented. Careful not to open any black holes!


The routine is relatively straightforward. To find the probabilities of $x=0, 1, \cdots, 5$ assuming a Poisson distribution with $\lambda=2$:

n = DINDGEN(6) probs = PMB_POISSON(n, 2)

Author information


Phillip M. Bitzer, University of Alabama in Huntsville, pm.bitzer "AT" uah.edu


Modification History:

First written: Sometime in 2012. Moved to the official stats repo; accordingly, the name has been changed. 20130129 PMB


top pmb_poisson_pdf

result = pmb_poisson_pdf(n, lambda)

For given value(s) of x, calculate the Poisson probability(ies).

Return value

The Poisson probability for each element in n.


n in required type=numeric scalar or array

The data you wish to calculate the Poission probability of. All values must be greater than or equal to zero.

lambda in required type=numeric scalar

The mean of of the Poisson distribution. Must be greater than zero.

File attributes

Modification date: Tue Mar 25 17:13:25 2014
Lines: 13
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