The Fractional Weights option is based on the Bayesian bootstrap (Rubin, 1981). The number of times that an observation occurs in a given bootstrap sample is called its bootstrap weight. In the simple bootstrap, the bootstrap weights for each bootstrap sample are determined using simple random sampling with replacement.
Randomly generate a vector of n values from a gamma distribution with shape parameter equal to (n - 1)/n and scale parameter equal to 1.
Compute S = sum of the n values.

Help created on 9/19/2017