Updated 24 Oct 2022
- boot returns resamples data or indices created by balanced bootstrap or bootknife resampling
- bootknife performs balanced bootknife resampling and calculates bootstrap bias, standard error and confidence intervals. The interval types supported are simple percentile, bias-corrected and accelerated, or calibrated percentile. This function supports iterated and stratified resampling.
- bootnhst calculates p-values by bootstrap null-hypothesis significance testing (two-tailed). This function can be used to compare 2 or more (independent) samples in designs with a one-way layout. This function resamples under the null hypothesis.
- bootmode uses bootstrap to evaluate the likely number of real modes in a distribution
- bootci is a function for calculating bootstrap confidence intervals. This function is a wrapper of the bootknife function but has the same usage as the bootci function from Matlab's Statistics and Machine Learning toolbox.
- bootstrp is a function for calculating bootstrap statistics. This function is a wrapper of the bootknife function but has the same usage as the bootstrp function from Matlab's Statistics and Machine Learning toolbox.
- Download the package. If it is a compressed file, decompress it.
- Open Octave or Matlab command prompt.
- cd to the package directory. (The directory contains a file called 'make.m' and 'install.m')
- Type make to compile the mex files from source (or use the precompiled binaries if available).
- Type install. The package will load now (and automatically in the future) when you start Octave/Matlab.
Andrew Penn (2022). statistics-bootstrap (https://github.com/gnu-octave/statistics-bootstrap/releases/tag/v5.0.2), GitHub. Retrieved .
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