Hi, I have a data set composed of several Gaussian kernels. I have a program that currently computes mutual information for all samples in the data set and also calculates mutual information for subsets at the extrema of the distribution. In the same program, I have a class that creates a vector of samples through sampling with replacement. I will still need to create an implementation that uses this replacement appropriately. Thus, I need to create a script that composes these data sets for bootstrapping. My question is, how will a bootstrapping algorithm effect the mutual information calculation for the samples at the extrema of the distribution? Furthermore, how exactly would I program such a bootstrapping implementation? Thanks!

In reply to Bootstrapping Implementation by hoffmann

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