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Ejemplo

Ejemplo. 0 4 1 3 2 4 3 5 4 2 5 4 6 3 7 4 8 5 9 1 10 4 11 3 12 4 13 5 14 2 15 4 16 3 17 4. Con N=18, encontrar el elemento que estaba en la posición 0 requiere 4 iteraciones; El de la posición 6, 3 iteraciones; etc., etc. Probemos con vectores más grandes:.

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Ejemplo

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  1. Ejemplo 0 4 1 3 2 4 3 5 4 2 5 4 6 3 7 4 8 5 9 1 10 4 11 3 12 4 13 5 14 2 15 4 16 3 17 4 Con N=18, encontrar el elemento que estaba en la posición 0 requiere 4 iteraciones; El de la posición 6, 3 iteraciones; etc., etc.

  2. Probemos con vectores más grandes:

  3. Buscando el ajuste perfecto con R* bbinaria = function(N) { m = floor(log2(N+1)) x = 1:m u = 2^(x-1) if (sum(u) < N) { p = c(u/N, 1-sum(u)/N) x = c(x, m+1) } else { p = u/N } return (list(x=x, p=p)) } T=1:100 T=500*T mu=array(NA, dim=100) for (i in 1:100) { F = bbinaria(T[i]) mu[i] = sum(F$x*F$p) } lT=log2(T) mod=lm(mu~lT) summary(mod) Coefficients: Estimate Std. Error t value Pr(>|t|) (Intercept) -0.986585 0.027777 -35.52 <2e-16 *** lT 1.003313 0.001946 515.65 <2e-16 *** Aproximadamente: mu = log(N) – 1 = log(N/2) * http://www.r-project.org/

  4. Pseudo-Random vs. True Random A Simple Visual Example http://www.boallen.com/random-numbers.html http://www.microsiervos.com/archivo/azar/ http://est-fib.blog.com/

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