Statistics.Resampling

A resample drawn randomly, with replacement, from a set of data points. Distinct from a normal array to make it harder for your humble author's brain to go wrong.

An estimator of a property of a sample, such as its mean.

The use of an algebraic data type here allows functions such as jackknife and bootstrapBCA to use more efficient algorithms when possible.

Run an Estimator over a sample.

Single threaded and deterministic version of resample.

O(e*r*s) Resample a data set repeatedly, with replacement, computing each estimate over the resampled data.

This function is expensive; it has to do work proportional to e*r*s, where e is the number of estimation functions, r is the number of resamples to compute, and s is the number of original samples.

To improve performance, this function will make use of all available CPUs. At least with GHC 7.0, parallel performance seems best if the parallel garbage collector is disabled (RTS option -qg).

Create vector using resamples

O(n) or O(n^2) Compute a statistical estimate repeatedly over a sample, each time omitting a successive element.

O(n) Compute the jackknife mean of a sample.

O(n) Compute the jackknife variance of a sample.

O(n) Compute the unbiased jackknife variance of a sample.

O(n) Compute the jackknife standard deviation of a sample.

Split a generator into several that can run independently.