BIB-VERSION:: CS-TR-v2.0
          ID:: STAN//CS-TR-72-254
       ENTRY:: October 16, 1995
ORGANIZATION:: Stanford University, Department of Computer Science
       TITLE:: Von Neumann's comparison method for random sampling from the
               normal and other distributions.
        TYPE:: Technical Report
      AUTHOR:: Forsythe, George E.
        DATE:: January 1972
       PAGES:: 21
    ABSTRACT:: The author presents a generalization he worked out in 1950 of
               von Neumann's method of generating random samples from the
               exponential distribution by comparisons of uniform random
               numbers on (0,1). It is shown how to generate samples from
               any distribution whose probability density function is
               piecewise both absolutely continuous and monotonic on
               ($-\infty$,$\infty$). A special case delivers normal deviates
               at an average cost of only 4.036 uniform deviates each. This
               seems more efficient than the Center-Tail method of Dieter
               and Ahrens, which uses a related, but different, method of
               generalizing the von Neumann idea to the normal distribution.
       NOTES:: [Adminitrivia V1/Prg/19951016]
         END:: STAN//CS-TR-72-254