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Dataplot Vol 2 Vol 1

ADEPPF

Name:
    ADEPPF (LET)
Type:
    Library Function
Purpose:
    Compute the asymmetric double exponential percent point function.
Description:
    The asymmetric double exponential distribution has the following percent point function:

      G(p,kappa) = (k/SQRT(2))*LOG[((1+kappa**2)/kappa**2)*p]
 0 < p < kappa**2/(1+kappa**2);
 = (-1/(kappa*SQRT(2)))*LOG[(1+kappa**2)*(1-p)] 
 kappa**2/(1+kappa**2) < p < 1;
 kappa > 0

    with kappa denoting the shape parameter.

    The standard asymmetric double exponential distribution can be generalized with a location parameter, theta, and a scale parameter sigma. Simply replace x with

      (x-theta)/sigma

    in the above formula.

    If kappa = 1 and the scale parameter = SQRT(2), the asymmetric double exponential distribution reduces to the symmetric double exponential distribution.

    The asymmetric double exponential distribution is also known as the asymmetric Laplace distribution.

Syntax:
    LET <y> = ADEPPF(<p>,<k>,<loc>,<scale>)
                            <SUBSET/EXCEPT/FOR qualification>
    where <p> is a variable, number or a parameter in the range (0,1);
                <k> is a positive number of parameter that specifies the value of the shape parameter;
                <loc> is an optional number or parameter that specifies the value of the location parameter;
                <scale> is an optional positive number or parameter that specifies the value of the scale parameter;
                <y> is a variable or a parameter (depending on what <x> is) where the computed asymmetric double exponential ppf value is stored;
    and where the <SUBSET/EXCEPT/FOR qualification> is optional.
Examples:
    LET Y = ADEPPF(0.95,1)
    LET Y = ADEPPF(P1,K)
    PLOT ADEPPF(P,K) FOR L = 0.01 0.01 0.99
Note:
    Kotz, Kozubowski, and Podgorski define an alternate parameterization based on the parameter mu. These parameterizations are related by:

      mu = (1/SQRT(2))*((1/k) - k)

      k  = SQRT(2)/(mu + SQRT(2 + mu**2))

    The mu parameter can be any real number. A value of mu = 0 reduces to the symmetric double exponential (i.e., kappa = 1).

    By default, Dataplot uses the kappa parameterization. To use the mu parameterization, enter the command

      SET ASYMMETRIC DOUBLE EXPONENTIAL DEFINITION MU

    To reset the kappa parameterization, enter the command

      SET ASYMMETRIC DOUBLE EXPONENTIAL DEFINITION K
Default:
    None
Synonyms:
    None
Related Commands:
    ADECDF = Compute the asymmetric double exponential cumulative distribution function.
    ADEPDF = Compute the asymmetric double exponential probability density function.
    SDEPDF = Compute the skew double exponential probability density function.
    DEXPDF = Compute the double exponential probability density function.
    EXPPDF = Compute the exponential probability density function.
    SNPDF = Compute the skew normal probability density function.
    STPDF = Compute the skew t probability density function.
Reference:
    "The Laplace Distribution and Generalizations: A Revisit with Applications to Communications, Economics, Engineering, and Finance", Birkhauser, 2001, pp. 133-174.

    "A Class of Distributions Which Includes the Normal Ones", Azzalini, Scandinavian Journal of Statistics, 12, 171-178.

Applications:
    Distributional Modeling
Implementation Date:
    6/2004
Program:
     
    X1LABEL Probability
    Y1LABEL X
    LABEL CASE ASIS
    TITLE CASE ASIS
    X1LABEL DISPLACEMENT 10
    CASE ASIS
    MULTIPLOT 2 2
    MULTIPLOT CORNER COORDINATES 0 0 100 95
    MULTIPLOT SCALE FACTOR 2
    TITLE Kappa = 0.5
    PLOT ADEPPF(P,0.5) FOR P = 0.01  0.01  0.99
    TITLE Kappa = 1
    PLOT ADEPPF(P,1) FOR P = 0.01  0.01  0.99
    TITLE Kappa = 2
    PLOT ADEPPF(P,2) FOR P = 0.01  0.01  0.99
    TITLE Kappa = 5
    PLOT ADEPPF(P,5) FOR P = 0.01  0.01  0.99
    END OF MULTIPLOT
    MOVE 50 97
    JUSTIFICATIONC CENTER
    TEXT Asymmetric Double Exponential Distribution
        
    plot generated by sample program

Date created: 7/7/2004
Last updated: 7/7/2004
Please email comments on this WWW page to alan.heckert@nist.gov.