# UAH LTG IDL Library

## IDL Routines from Phillip Bitzer and UAH Lightning Group

summary     class     fields     routine details     file attributes

# pmb_poisson_pdf.pro

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!

## Examples

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

Author

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

History

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.

### Parameters

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 Docformat: rst rst