This function resamples under the null hypothesis. This function can be used to compare 2 or more (independent) samples.

ibootnhst calculates p-values by bootstrap null-hypothesis significance testing (two-tailed).

ibootp calculates a two-tailed p-value for hypothesized value of the statistic using bootstrap.

ibootci calculates confidence intervals (calibrated) by iterated bootstrap resampling.

bootci calculates confidence intervals using bootstrap resampling.

bootknife performs (balanced) bootknife resampling.

bootstrp performs (balanced) bootstrap resampling.

In Octave, you can find out basic information about the package by typing: pkg describe -verbose statistics-bootstrap Usage Functions The package can be loaded on demand in Octave with the following commmand: To uninstall, follow the above steps but use the uninstall commandĪlternatively, users of more recent versions of Octave can install the package automatically with the following command: The package will load now and automatically when you start Octave/Matlab (The directory contains a file called 'install.m') If it is a compressed file, decompress it. To install (or test) the statistics-bootstrap package at it's existing location in either Octave or Matlab, follow these steps: An exception is the parallel computing options, which require either the Octave forge parallel package or the Parallel Computing Matlab Toolbox.

Most features of of the package do not depend on other packages. This package is known to be compatible with versions of Octave v3.6.0+ and Matlab v7.4.0+. The Octave statistics-bootstrap package is forked from the GitHub repository iboot. Variations of the bootstrap are included that improve the accuracy of bootstrap statistics for small samples and samples with complex dependence structures.

This package of functions can be used to estimate uncertainty (confidence intervals) and test hypotheses ( p-values) using bootstrap. Ī statistics package for Octave/Matlab providing a variety of bootstrap resampling tools iboot: Iterated bootstrap for small samples or samples with complex dependence structures. If you use this package please include the following citation(s): Statistics-bootstrap package Package maintainer

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