statistics-resampling

Version 5.6.0 (328 KB) by Andrew Penn
Statistical analysis using resampling methods
5.0
(5)
819 Downloads
Updated 17 Jun 2024
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Cite As

Penn, Andrew Charles. Resampling Methods for Small Samples or Samples with Complex Dependence Structures [Https://Github.com/Gnu-Octave/Statistics-Resampling/]. Zenodo, 2020, doi:10.5281/ZENODO.3992392.

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Version Published Release Notes
5.6.0

See release notes for this release on GitHub: https://github.com/gnu-octave/statistics-resampling/releases/tag/5.6.0
5.5.18

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5.5.17

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5.5.16

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5.5.15

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5.5.14

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5.5.13

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5.5.12

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5.5.11

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5.5.10

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5.5.9

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5.5.8

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5.5.7

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5.5.6

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5.5.5

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5.5.4

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5.5.3

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5.5.2

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5.5.1

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5.5.0

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5.4.4

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5.4.3

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5.4.2.0

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5.4.1.0

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5.4.0.0

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5.3.5.0

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5.3.3.0

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5.3.2.0

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5.3.1.0

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5.3.0.0

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5.2.8.0

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5.2.7.0

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5.2.6.0

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5.2.5.0

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5.2.4.0

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5.2.3.0

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5.2.2.0

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5.2.1.0

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5.2.0.0

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5.1.6.0

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5.1.5.0

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5.1.4.0

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5.1.3.0

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5.1.2.0

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5.1.1.0

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5.1.0.0

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5.0.2

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5.0.1

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5.0.0

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4.2.0

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4.1.1

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4.1.0.0

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4.0.0.0

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3.10.2.0

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3.10.1.0

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3.9.3.0

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3.9.2.0

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3.9.1.0

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3.8.1.0

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3.8.0.0

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3.7.16.0

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3.7.15.0

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3.7.14.0

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3.7.13.0

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3.7.12.0

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3.7.11.0

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3.7.10.0

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3.7.9.0

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3.7.8.0

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3.7.7.0

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3.7.6.0

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3.7.5.0

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3.7.4.0

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3.7.3.0

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3.7.2.0

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3.7.1.0

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3.7.0.0

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3.6.10.0

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3.6.9.0

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3.6.8.0

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3.6.7.0

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3.6.6.0

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3.6.5.0

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3.6.4.0

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3.6.3.0

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3.6.2.0

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3.6.1.0

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3.6.0.0

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3.5.1.0

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3.5.0.0

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3.4.0.0

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3.3.9.0

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3.3.8.0

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3.3.5.0

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3.3.4.0

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3.3.2.0

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3.3.1.0

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3.3.0.0

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3.2.4.0

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3.2.2.0

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3.2.1.0

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3.2.0.0

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3.1.7.0

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3.1.6.0

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3.1.5.0

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3.1.4.0

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3.1.3.0

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3.1.2.0

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3.1.1.0

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3.1.0.0

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3.0.3.0

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3.0.2.0

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2.9.2.0

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2.9.1.0

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2.9.0.0

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2.8.8.0

Set random seed to make ibootci deterministic when running in serial mode. modified code to make computation of random permutations the same between Matlab and Octave. Updated DOI for all versions

2.8.7.5

Corrected citation
2.8.7.4

Updated citation
2.8.7.3

added DOI to citation
2.8.7.2

Corrected bug in double block bootstrap: Second block bootstrap resampling no longer samples across the block joints of the first bootstrap sample sets.
2.8.7.1

Fixed bug that prevented calculation of BCa intervals for Block bootstrap and made calculations of acceleration constant (for BCa intervals) erroneous for bootstrapping clustered data.
2.8.7.0

Added BCa intervals for all types of bootstrap sampling (ordinary, weighted, block, cluster etc.). Bug fix for cluster bootstrap resampling. Added parallel computing capabilities for Octave. Subfunctions moved into function files in iboot package.
2.8.4.2

Now includes bias-corrected percentile intervals
2.8.3.5

Added the option for smoothing the bootstrap to improve interval coverage for small smples. Removed BCa type intervals since these can be unreliable for small samples.
2.8.1.0

Parallel implementation of ibootci now works for all resampling options (with the only difference being that the first level bootstrap uses ordinary resampling with replacement instead of balanced resampling)
2.8.0.0

Added support for accelerating calculations by performing computations in parallel across CPUs. Made calculations of design effect optional.
2.7.9.6

Minor bug fix for DEFF calculation after Block and Cluster bootstrap.
2.7.9.4

Now includes a new optional input argument 'stderr' for provision of a function handle to calculate standard errors for Studentized intervals (instead of using bootstrap iteration). Also includes minor bug fixes.
2.7.9.0

Minor changes to syntax to provide backwards compatibility back to R2007A
2.7.6.0

For cluster resampling option, balanced resampling now occurs at the level of cluster means. Resampling now used to estimate design effect across the full range of input options. Minor bug fixes.

2.7.0.0

Wild bootstrap removed since it is now superseded by pairs bootstrap, which is implemented with double bootstrap and is compatible with block resampling. Corrected bootidx output argument for block resampling.
2.6.0.0

Now includes an option to perform Wild bootstrap, compatible with BCa intervals but not bootstrap iteration. Output structure includes autocorrelation results to examine the assumption of i.i.d.
2.5.0.0

Improved algorithm for block bootstrap. Now combines circular, overlapping blocks with the double bootstrap approach of Lee and Lai (2009); the calibration method makes interval coverage less sensitive to the choice of block length.
2.4.0.0

Added capability for block bootstrap of dependent data (e.g. time series)
2.3.7.0

Improved the coverage of cluster bootstrap for unbalanced cluster sizes.
2.3.4.0

Trimmed output structure down to providing only necessary information
2.3.2.0

Corrected calculation of ICC for output structure S
2.3.0.0

Now includes capability to perform two-stage nonparametric bootstrap sampling with shrinkage correction for clustered data
2.2.2.0

Made calculation of SSE components of stratified data (provided as descriptive statistics in output structure S) compatible with multivariate data. Now also returns the degrees of freedom.
2.2.0.0

Changed default interval type to BCa to be consistent with bootci. Corrected some comments and function help.
2.1.0.1

Added extra tags to the webpage
2.1.0.0

Now supports calculation confidence intervals using the bootstrap-t method. Standard errors of the bootstrap samples are determined by double bootstrap.
2.0.0.0

This new version can also perform stratified bootstrap resampling.
1.9.0.0

If bootstrap iteration is requested, bootstat returns: boostat statistics from both 1st and 2nd bootstrap; the double bootstrap bias and bias-corrected statistic in S; and, the double boostrap corrected standard error of the statistic in S.

1.8.4.0

Added a check for successful calculation of the acceleration constant for the BCa intervals
1.8.3.0

Corrected the check for when bootstrap confidence intervals hit the ends of the bootstrap distribution
1.8.2.0

Updated title and summary
1.8.1.0

Linked to Github
1.8.0.0

Moved to Github. Calibration and interval construction carried out by interpolating from the empirical distribution function. Minor performance improvement by avoiding a sort in the second bootstrap. Coverage confirmed with simulations.

1.7.1.0

Performance enhancement for the second bootstrap through alternative execution of randperm
1.7.0.0

Included error message when second bootstrap replicate size is insufficient for the desired alpha. Minor improvement to the calibration included. Changed output arguments: Now includes output structure (of settings and results) and calibration curve.
1.6.3.0

Added back a warning for when the resulting intervals hit the end(s) of the bootstrap distribution
1.6.2.6

Corrected typos (missing % signs) in the comments of the examples in the description
1.6.2.5

Updated image icon
1.6.2.4

Adjusted icon image dimensions
1.6.2.3

Adjusted icon image dimensions
1.6.2.2

Adjusted icon image size
1.6.2.1

Minor update to function description. Added image icon.
1.6.2

Swapped the order of output arguments to match Matlabs bootci
1.6.1

Set default bootstrap type to percentile.
1.6

Added the ability to use different types of intervals: percentile or BCa. The BCa type interval is the default.
1.5.4.2

Made minor changes to the description and to the function help
1.5.4.1

Corrected description
1.5.4.0

Added the capability to use bootidx input when calculating bootstrap confidence for multivariate data. Modified default values for nboot
1.5.3.3

Clarified some of the help/comments and included another example of it's usage for calculating confidence intervals for the median
1.5.3.2

Updated some comments
1.5.3.1

Modified default values for the number of bootstrap samples

1.5.3.0

Modified the implementation with weights based on simulation results
1.5.2.1

Updated the help comments
1.5.2.0

Fixed a bug preventing some function usage. Added back the ability to use functions (in the bootfun input argument) that do not output a row vector for matrix input argument(s) (e.g. 'corr' function).
1.5.1.1

Removed depreciated lines of code
1.5.1.0

Implemented appropriated weight allocation for the second bootstrap
1.5.0.0

Added interpolation also to the first bootstrap. Performance improvements made to the resampling algorithm. Added feature to provide weights to modify sampling probabilities.
1.4.1.0

Corrected a mistake presented in example 3 (in comment only).

1.4.0.0

1.4.0.0 - Implementation modified for less memory footprint. Algorithm now uses balanced resampling. Coverage is calibrated using the interpolation method instead of the approximate Monte Carlo method. Also returns bias of the bootstrap.

1.3.0.0

Simplified title
Included example usage in the function help
1.2.0.0

Now less stringent data requirements. Data can be row vectors or column vectors
1.1.0.0

Now checks the dimensions of the data
1.0.0.0

To view or report issues in this GitHub add-on, visit the GitHub Repository.
To view or report issues in this GitHub add-on, visit the GitHub Repository.