C Library Functions  - poiplt (3)

NAME
poiplt(3f) - [M_datapac:LINE_PLOT] generate a Poisson probability plot (line printer graph)

CONTENTS

Synopsis
Description
Options
Examples
Author
Maintainer
License
References

SYNOPSIS
SUBROUTINE POIPLT(X,N,Alamba)

DESCRIPTION
poiplt(3f) generates a poisson probability plot (with REAL tail length parameter = alamba).

the prototype poisson distribution used herein has mean = alamba and standard deviation = sqrt(alamba).

this distribution is defined for all discrete non-negative integer x--x = 0, 1, 2, ... .

this distribution has the probability function 

       f(x) = exp(-alamba) * alamba**x / x!.
the poisson distribution is the distribution of the number of events in the interval (0,alamba) when the waiting time between events is exponentially distributed with mean = 1 and standard deviation = 1.

the prototype distribution restrictions of discreteness and non-negativeness mentioned above do not carry over to the input vector x of observations to be analyzed.

the input observations in x may be discrete, continuous, non-negative, or negative.

as used herein, a probability plot for a distribution is a plot of the ordered observations versus the order statistic medians for that
distribution.
  the poisson probability plot is useful in graphically testing the composite (that is, location and scale parameters need not be specified) hypothesis that the underlying distribution from which the data have been randomly drawn is the poisson distribution with tail length parameter value = alamba.
if the hypothesis is true, the probability plot should be near-linear.

a measure of such linearity is given by the calculated probability plot correlation coefficient.

OPTIONS
X description of parameter
Y description of parameter

EXAMPLES
Sample program: 

   program demo_poiplt
   use M_datapac, only : poiplt
   implicit none
   ! call poiplt(x,y)
   end program demo_poiplt
Results:

AUTHOR
The original DATAPAC library was written by James Filliben of the Statistical Engineering Division, National Institute of Standards and Technology.

MAINTAINER
John Urban, 2022.05.31

LICENSE
CC0-1.0

REFERENCES
o FILLIBEN, ’TECHNIQUES FOR TAIL LENGTH ANALYSIS’, PROCEEDINGS OF THE

    EIGHTEENTH CONFERENCE ON THE DESIGN OF EXPERIMENTS IN ARMY RESEARCH
DEVELOPMENT AND TESTING (ABERDEEN, MARYLAND, OCTOBER, 1972), pages 425-450.
o HAHN AND SHAPIRO, STATISTICAL METHODS IN ENGINEERING, 1967, pages 260-308.
o JOHNSON AND KOTZ, DISCRETE DISTRIBUTIONS, 1969, pages 87-121.

Nemo Release 3.1 poiplt (3) February 23, 2025
Generated by manServer 1.08 from 5f7cbddc-fd97-4623-898d-2fd5a2ee0f5f using man macros.