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Luis A. Afonso
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4,526
From:
LIsbon (Portugal)
Registered:
2/16/05


Not to achieve CDF inversion doesn´t matter
Posted:
Sep 5, 2012 12:13 PM


Not to achieve CDF inversion doesn´t matter
A very recent reading, Author: Samik Raychaudhury
www.informssim.org/wsc08papers/012.pdf
I could notice about an ?iterative method? the author gives in order to get samples from a given cdf F(x) (cumulative distribution function) to which an algebraic inversion is impossible to be performed. A method I ordinary use is based on loops (say 3) in each one the steps are got narrower and narrower, for example st0 = .5, st1=0.01*st0, st2=0.01*st1. The procedure goes as: __1__Given a RND=y0 we start from the origin (relative to the loop) and proceed calculating, with step= stk as long that F(x) is less than y0. This value just exceeded (x´´) one pass to the following loop. Except for the first loop the origin is set at x´´ 1.05*stk. __2__The final x´´ is a very close to that make F(x´´)= y0 as I could state by an Finvertible example.
Example A Gambel distribution has _____F(x) = Exp (Exp (1x)/2)) From 100000 random numbers we find that circa 0.7 % values the difference from the exact values is less than 0.000010 (!), the exact being obtained from the inversion : x = 1  2* Log(Log(y0)). Note that using a more elaborated language than Basic this exactness could be much better
Luis A. Afonso



