lgnplt(3f) - [M_datapac:LINE_PLOT] generates a lognormal probability plot
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SUBROUTINE LGNPLT(X,N)
lgnplt(3f) generates a lognormal probability plot.the prototype lognormal distribution used herein has mean = sqrt(e) = 1.64872127 and standard deviation = sqrt(e*(e-1)) = 2.16119742. this distribution is defined for all positive x and has the probability density function
f(x) = (1/(x*sqrt(2*pi))) * exp(-log(x)*log(x)/2)the prototype lognormal distribution used herein is the distribution of the variate x = exp(z) where the variate z is normally distributed with mean = 0 and standard deviation = 1.
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 lognormal 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 lognormal 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.
X description of parameter Y description of parameter
Sample program:
program demo_lgnplt use M_datapac, only : lgnplt implicit none ! call lgnplt(x,y) end program demo_lgnpltResults:
The original DATAPAC library was written by James Filliben of the Statistical Engineering Division, National Institute of Standards and Technology.
John Urban, 2022.05.31
CC0-1.0
o FILLIBEN, TECHNIQUES FOR TAIL LENGTH ANALYSIS, PROCEEDINGS OF THE
DEVELOPMENT AND TESTING (ABERDEEN, MARYLAND, OCTOBER, 1972), pages 425-450.
o |
HAHN AND SHAPIRO, STATISTICAL METHODS IN ENGINEERING, 1967, pages
260-308.
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Nemo Release 3.1 | lgnplt (3) | February 23, 2025 |