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B12PPFName:
with c and k denoting the shape parameters. This distribution can be generalized with location and scale parameters in the usual way using the relation
The Burr type 12 distribution is also sometimes referred to as the Singh-Maddala distribution.
<SUBSET/EXCEPT/FOR qualification> where <p> is a number, parameter, or variable in the interval (0,1); <y> is a variable or a parameter (depending on what <p> is) where the computed Burr type 12 ppf value is stored; <c> is a positive number, parameter, or variable that specifies the first shape parameter; <k> is a positive number, parameter, or variable that specifies the second shape parameter; <loc> is a number, parameter, or variable that specifies the location parameter; <scale> is a positive number, parameter, or variable that specifies the scale parameter; and where the <SUBSET/EXCEPT/FOR qualification> is optional. If <loc> and <scale> are omitted, they default to 0 and 1, respectively.
LET Y = B12PPF(X,0.5,2.2,0,5) PLOT B12PPF(P,2.3,1.4) FOR P = 0.01 0.01 0.99
Johnson, Kotz, and Balakrishnan (1994), "Contiunuous Univariate Distributions--Volume 1", Second Edition, Wiley, pp. 53-54. Devroye (1986), "Non-Uniform Random Variate Generation", Springer-Verlang, pp. 476-477.
LABEL CASE ASIS TITLE CASE ASIS TITLE OFFSET 2 . MULTIPLOT 4 4 MULTIPLOT CORNER COORDINATES 0 0 100 95 MULTIPLOT SCALE FACTOR 4 . LET CVAL = DATA 0.5 1 2 5 LET KVAL = DATA 0.5 1 2 5 . LOOP FOR IROW = 1 1 4 LOOP FOR ICOL = 1 1 4 LET C = CVAL(IROW) LET K = KVAL(ICOL) TITLE C = ^c, K = ^k PLOT B12PPF(P,C,K) FOR P = 0.01 0.01 0.99 END OF LOOP END OF LOOP . END OF MULTIPLOT . JUSTIFICATION CENTER MOVE 50 97 TEXT Burr Type 12 Percent Point Functions
Date created: 12/17/2007 |