GETCDF

GETCDF (LET)

Library Function

Compute the Geeta cumulative distribution function.

The Geeta distribution has the following probability mass function:

with and denoting the shape parameters.

The mean and variance of the Geeta distribution are:

=

² =

The Geeta distribution is sometimes parameterized in terms of its mean, , instead of . This results in the following probability mass function:

For this parameterization, the variance is

² =

This probability mass function is also given in the form:

Dataplot supports both parameterizations (see the Note section below).

The cumulative distribution function is computed by summing the probability mass function.

LET <y> = GETCDF(<x>,<shape>,<beta>)
                        <SUBSET/EXCEPT/FOR qualification>
where <x> is a positive integer variable, number, or parameter;
            <shape> is a number, parameter, or variable that specifies the valuie of theta (or mu);
            <beta> is a number, parameter, or variable that specifies the second shape parameter;
            <y> is a variable or a parameter (depending on what <x> is) where the computed Geeta cdf value is stored;
and where the <SUBSET/EXCEPT/FOR qualification> is optional.

LET A = GETCDF(3,0.5,1.4)
LET Y = GETCDF(X,0.3,1.6)
PLOT GETCDF(X,0.3,1.6) FOR X = 1 1 20

To use the MU parameterization, enter the command
SET GEETA DEFINITION MU

To restore the THETA parameterization, enter the command

SET GEETA DEFINITION THETA

None

None

GETPDF	= Compute the Geeta probability mass function.
GETPPF	= Compute the Geeta percent point function.
CONPDF	= Compute the Consul probability mass function.
GLSPDF	= Compute the generalized logarithmic series probability mass function.
DLGPDF	= Compute the logarithmic series probability mass function.
YULPDF	= Compute the Yule probability mass function.
ZETPDF	= Compute the Zeta probability mass function.
BGEPDF	= Compute the beta geometric probability mass function.
POIPDF	= Compute the Poisson probability mass function.
BINPDF	= Compute the binomial probability mass function.

Consul and Famoye (2006), "Lagrangian Probability Distribution", Birkhauser, chapter 8.

Consul (1990), "Geeta Distribution and its Properties", Communications in Statistics--Theory and Methods, 19, pp. 3051-3068.

Distributional Modeling

2006/8

 
set geeta definition theta
title size 3
tic label size 3
label size 3
legend size 3
height 3
x1label displacement 12
y1label displacement 15
.
multiplot corner coordinates 0 0 100 95
multiplot scale factor 2
label case asis
title case asis
case asis
tic offset units screen
tic offset 3 3
title displacement 2
y1label Probability
x1label X
.
ylimits 0 1
major ytic mark number 6
minor ytic mark number 3
xlimits 0 20
line blank
spike on
.
multiplot 2 2
.
title Theta = 0.3, Beta = 1.8
plot getcdf(x,0.3,1.8) for x = 1 1 20
.
title Theta = 0.5, Beta = 1.5
plot getcdf(x,0.5,1.5) for x = 1 1 20
.
title Theta = 0.7, Beta = 1.2
plot getcdf(x,0.7,1.2) for x = 1 1 20
.
title Theta = 0.9, Beta = 1.1
plot getcdf(x,0.9,1.1) for x = 1 1 20
.
end of multiplot
.
justification center
move 50 97
text Cumulative Distributions for Geeta Distribution