 Dataplot Vol 2 Vol 1

# GHPPF

Name:
GHPPF (LET)
Type:
Library Function
Purpose:
Compute the g-and-h percent point function.
Description:
The percent point function of the g-and-h distribution is defined as follows: with Zp denoting the normal percent point function of p. When g = 0 and h = 0, the g-and-h distribution reduces to a standard normal distribution.

The value of g controls the degree of skewness. For g = 0, the distribution is symmetric. As the absolute value of g increases, the amount of the skewness increases. The sign of g controls the direction of the skewness (but not the amount). Positive values of g skew the distribution to the right tail while negative values of g skew the distribution to the left tail. Values for g are typically in the range (-1,1).

The value of h controls the elongation, or how heavy the tails are, of the distribution. For h = 0, the elongation is equivalent to that of a normal distribution. For h = 1, the elongation is equivalent to that of a Cauchy distribution. Values of h are typically in the range (0,1).

Specifying values for both g and h gives this distribution great flexibility in modeling data.

The input value is a real number between 0 and 1 (since it corresponds to a probability).

The g-and-h distribution can be generalized with location and scale parameters in the usual way.

Syntax:
LET <y> = GHPPF(<p>,<g>,<h>,<loc>,<scale>)
<SUBSET/EXCEPT/FOR qualification>
where <p> is a variable, number, or parameter in the range 0 to 1;
<g> is a number or parameter that specifies the skewness shape parameter;
<h> is a number or parameter that specifies the elongation shape parameter;
<loc> is a number or parameter that specifies the location parameter;
<scale> is a number or parameter that specifies the scale parameter;
<y> is a variable or a parameter (depending on what <p> is) where the computed g-and-h ppf value is stored;
and where the <SUBSET/EXCEPT/FOR qualification> is optional.

Note that the location and scale parameters are optional.

Examples:
LET A = GHPPF(0.95,0.5,0.2)
LET Y = GHPPF(P,0.5,0.2)
PLOT GHCDF(P,0.5,0.2) FOR P = 0.01 0.01 0.01
Default:
None
Synonyms:
None
Related Commands:
 GHCDF = Compute the g-and-h cumulative distribution function. GHPDF = Compute the g-and-h probability density function. LAMPDF = Compute the Tukey-Lambda probability density function. NORPDF = Compute the standard normal probability density function. LOGPDF = Compute the logistic probability density function. JSUPDF = Compute the Johnson SU probability density function.
Reference:
"Summarizing Shape Numerically: The g-and-h Distributions", David C. Hoaglin, chapter 11 in "Exploring Data Tables, Trends, and Shapes", Eds. Hoaglin, Mosteller, and Tukey, Wiley, 1985.
Applications:
Distributional Modeling
Implementation Date:
2004/5
Program:
```
MULTIPLOT 2 2
MULTIPLOT SCALE FACTOR 2
MULTIPLOT CORNER COORDINATES 0 0 100 95
Y1LABEL X
X1LABEL PROBABILITY
X1LABEL DISPLACEMENT 12
Y1LABEL DISPLACEMENT 12
TITLE G = 0.2, H = 0.2
PLOT GHPPF(P,0.2,0.2) FOR P = 0.01 .01 0.99
TITLE G = 0.5, H = 0.2
PLOT GHPPF(P,0.5,0.2) FOR P = 0.01 .01 0.99
TITLE G = 0.2, H = 0.5
PLOT GHPPF(P,0.2,0.5) FOR P = 0.01 .01 0.99
TITLE G = 0.5, H = 0.5
PLOT GHPPF(P,0.5,0.5) FOR P = 0.01 .01 0.99
END OF MULTIPLOT
MOVE 50 97
JUSTIFICATION CENTER
TEXT G-AND-H DISTRIBUTIONS
``` Date created: 7/7/2004
Last updated: 7/7/2004