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C Library Functions  - logplt (3)

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NAME

logplt(3f) - [M_datapac:LINE_PLOT] generate a logistic probability plot

CONTENTS

Synopsis
Description
Input Arguments
Output
Examples
Author
Maintainer
License
References

SYNOPSIS

SUBROUTINE LOGPLT(X,N)

       INTEGER,intent(in) :: N
       REAL(kind=wp),intent(in) :: X(:)

DESCRIPTION

LOGPLT(3f) generates a logistic probability plot.

The prototype logistic distribution used herein has mean = 0 and standard deviation = pi/sqrt(3). This distribution is defined for all X and has the probability density function

       f(X) = exp(X) / (1+exp(X))

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 logistic 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 logistic distribution.

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.

INPUT ARGUMENTS

X	The vector of (unsorted or sorted) observations.
N	The integer number of observations in the vector X. The maximum allowable value of N for this subroutine is 7500.

OUTPUT

A one-page logistic probability plot.

EXAMPLES

Sample program:

   program demo_logplt
   use M_datapac, only : logplt
   implicit none
   ! call logplt(x,y)
   end program demo_logplt

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, Continuous Univariate Distributions--2, 1970, pages 1-21.

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Nemo Release 3.1

logplt (3)

July 22, 2023

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