Unformatted text preview: the inverse CDF solving the CDF in terms of x. This is then used to decipher the distribution of F. When performing the inverse CDF algorithm, we first integrate pdf to receive the CDF. We then have the CDF equal to y. We then isolate for x, so as to have an equation in terms of y. This is the inverse of CDF. This is then implemented into R to find the mean, median and variance of the x values. The work is shown below. R-code: > u=runif(1000) > x=5*((-log(1-u))^1/4) > mean(x)  1.261994 > median(x)  0.8143902 > var(x)  1.670796...
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- Spring '08
- Variance, Probability theory, probability density function, Cumulative distribution function, CDF