GGDCHAZ
Name:
Type:
Purpose:
Compute the standard form of the generalized gamma cumulative
hazard function.
Description:
The standard form of the generalized gamma distribution has the
following cumulative hazard function:
where k and c are shape parameters and GGDCDF is the cumulative
distribution function of the generalized gamma distribution.
Syntax:
LET <y> = GGDCHAZ(<x>,<k>,<c>)
<SUBSET/EXCEPT/FOR qualification>
where <x> is a positive number, parameter, or a variable;
<y> is a variable or a parameter (depending on what
<x> is) where the computed generalized gamma
cumulative hazard value is saved;
<k> is a positive number, parameter, or variable that
specifies the first shape parameter;
<c> is a non-zero number, parameter, or variable that
specifies the second shape parameter;
and where the <SUBSET/EXCEPT/FOR qualification> is optional.
Examples:
LET A = GGDCHAZ(3,1.5.0.6)
LET X2 = GGDCHAZ(X1,GAMMA,POWER)
Note:
If c is 1, this distribution reduces to the standard gamma
distribution. If k is 1, this distribution reduces to a Weibull
distribution. If k =1/2 and c = 2, it reduces to a half-normal
distribution. Several other common distributions are special
cases of the generalized gamma distribution.
The second shape parameter can be negative (but not zero).
Specifically, if c = -1, the generalized gamma reduces to the
inverted gamma distribution.
Default:
Synonyms:
Related Commands:
GGDCDF
|
= Compute the generalized gamma cumulative distribution
function.
|
GGDPDF
|
= Compute the generalized gamma probability density
function.
|
GGDPPF
|
= Compute the generalized gamma percent point function.
|
GGDHAZ
|
= Compute the generalized gamma hazard function.
|
GAMPDF
|
= Compute the gamma probability density function.
|
IGAPDF
|
= Compute the inverted gamma probability density function.
|
WEIPDF
|
= Compute the Weibull probability density function.
|
EXPPDF
|
= Compute the exponential probability density function.
|
CHSPDF
|
= Compute the chi-square probability density function.
|
Reference:
"Continuous Univariate Distributions", 2nd. ed., Johnson, Kotz,
and Balakrishnan, John Wiley and Sons, 1994 (chapter 17).
"Statistical Distributions", 2nd. Edition, Evans, Hastings, and
Peacock, Wiley and Sons, 1993 (chapter 18).
Applications:
Implementation Date:
Program:
LET G = DATA 1 1 1 0.5 0.5 0.5 2 2 2
LET C = DATA 0.5 1 2 0.5 1 2 0.5 1 2
LET START = DATA 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.01
LET INC = DATA 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.01
LET STOP = DATA 5 5 5 5 5 5 5 5 5
.
MULTIPLOT 3 3; MULTIPLOT CORNER COORDINATES 0 0 100 100
TITLE AUTOMATIC
LOOP FOR K = 1 1 9
LET G1 = G(K)
LET C1 = C(K)
LET FIRST = START(K)
LET LAST = STOP(K)
LET INCT = INC(K)
X1LABEL GAMMA = ^G1
X2LABEL C = ^C1
PLOT GGDCHAZ(X,G1,C1) FOR X = FIRST INCT LAST
END OF LOOP
END OF MULTIPLOT
Date created: 10/9/2001
Last updated: 4/4/2003
Please email comments on this WWW page to
alan.heckert@nist.gov.
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