
GMCPPFName:
with K_{}(.) denoting the modified Bessel function of the of the second kind of order and denoting the gamma function. The standard generalized McLeish distribution can be generalized with location and scale parameters in the usual way. The cumulative distribution function is computed by numerically integrating the probability density function. Dataplot performs the integration using the DQAG routine from the Slatec library. The percent point function is then computed by numerically inverting the cumulative distribution function using the DFZERO subroutine from the Slatec library.
<SUBSET/EXCEPT/FOR qualification> where <p> is a variable, a number, or a parameter; <alpha> is a positive number of parameter that specifies the value of the first shape parameter; <a> is a positive number of parameter that specifies the value of the second 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 generalized McLeish ppf value is stored; and where the <SUBSET/EXCEPT/FOR qualification> is optional.
LET Y = GMCPPF(P1,ALPHA,A) PLOT GMCPPF(P,ALPHA,A) FOR P = 0.01 0.01 0.99
X1LABEL Probability Y1LABEL X LABEL CASE ASIS TITLE CASE ASIS CASE ASIS Y1LABEL DISPLACEMENT 16 MULTIPLOT 2 2 MULTIPLOT CORNER COORDINATES 0 0 100 95 MULTIPLOT SCALE FACTOR 2 LET A = 0.8 TITLE Alpha = 1.5, A = 0.8 PLOT GMCPPF(P,1.5,A) FOR P = 0.01 0.01 0.99 LET A = 0.8 TITLE Alpha = 1.5, A = 0.8 PLOT GMCPPF(P,1.5,A) FOR P = 0.01 0.01 0.99 LET A = 0.2 TITLE Alpha = 1.5, A = 0.2 PLOT GMCPPF(P,1.5,A) FOR P = 0.01 0.01 0.99 LET A = 0.2 TITLE Alpha = 1.5, A = 0.2 PLOT GMCPPF(P,1.5,A) FOR P = 0.01 0.01 0.99 END OF MULTIPLOT MOVE 50 97 JUSTIFICATION CENTER TEXT Generalized McLeish Percent Point Function
Date created: 4/19/2005 