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feat: add stats/base/dists/bradford/entropy #5324

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merged 8 commits into from
Feb 22, 2025
Merged

feat: add stats/base/dists/bradford/entropy #5324

merged 8 commits into from
Feb 22, 2025

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@anandkaranubc anandkaranubc commented Feb 19, 2025 •
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Progresses #168

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  • Adds the JS implementation of the differential entropy of a Bradford distribution.

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@stdlib-bot stdlib-bot added Statistics Issue or pull request related to statistical functionality. Needs Review A pull request which needs code review. labels Feb 19, 2025
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stdlib-bot commented Feb 19, 2025 •
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Coverage Report

Package Statements Branches Functions Lines
stats/base/dists/bradford/entropy $\color{green}117/117$
$\color{green}+100.00\%$ 		$\color{green}6/6$
$\color{green}+100.00\%$ 		$\color{green}1/1$
$\color{green}+100.00\%$ 		$\color{green}117/117$
$\color{green}+100.00\%$

The above coverage report was generated for the changes in this PR.

anandkaranubc
anandkaranubc commented Feb 19, 2025
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lib/node_modules/@stdlib/stats/base/dists/bradford/entropy/test/test.js Outdated
Comment on lines 83 to 89
/*
* NOTE: the tolerance is set high in this case due to:
*
* 1. The shape parameter being very small which causes differences in the nested log expression compared to the reference (SciPy) implementation.
* 2. The expected values being either very small.
*/
tol = 1523.0 * EPS * abs( expected[ i ] );
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I tested it using both log1p and ln. The version with ln requires a "lower" tolerance than the one with log1p.

I also checked SciPy's implementation, and they use np.log in their implementation.

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Planeshifter approved these changes Feb 22, 2025
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Looks all good.

Compared Scipy implementation to the one in this PR and the formula is the same; difference must indeed arise from slight divergence in our log to np.log.

@Planeshifter Planeshifter added the Ready To Merge A pull request which is ready to be merged. label Feb 22, 2025
@stdlib-bot stdlib-bot removed the Needs Review A pull request which needs code review. label Feb 22, 2025
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PR Commit Message

feat: add `stats/base/dists/bradford/entropy`

PR-URL: https://github.com/stdlib-js/stdlib/pull/5324

Co-authored-by: Karan Anand <anandkarancompsci@gmail.com>
Reviewed-by: Philipp Burckhardt <pburckhardt@outlook.com>

Please review the above commit message and make any necessary adjustments.

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Looks all good.

Compared Scipy implementation to the one in this PR and the formula is the same; difference must indeed arise from slight divergence in our log to np.log.

I am also looking into whether there have been any changes in the upstream implementations of our ln function. I will keep you posted on that.

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Also, using Math.log instead does make a difference and reduces the tolerance thresholds.

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Also, using Math.log instead does make a difference and reduces the tolerance thresholds.

Interesting! How much can the tolerances be adjusted when using Math.log? Thanks for looking into whether there should be any changes made to our ln function.

cc @kgryte

@Planeshifter Planeshifter merged commit e8330ca into stdlib-js:develop Feb 22, 2025
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anandkaranubc commented Feb 22, 2025 •
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@Planeshifter From 1523.0 to 980.0 here

@anandkaranubc anandkaranubc deleted the bradford/entropy branch February 22, 2025 03:13
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kgryte commented Feb 22, 2025

@anandkaranubc You should also check against OpenLibm: https://github.com/JuliaMath/openlibm/blob/master/src/e_log.c

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RFC: add the Bradford distribution
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