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test: migrate stats/base/dists/pareto-type1/logpdf to ULP-based assertions - #14842

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test: migrate stats/base/dists/pareto-type1/logpdf to ULP-based assertions#14842
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Resolves a part of #11352.

Description

What is the purpose of this pull request?

This pull request:

  • Migrates the tests for @stdlib/stats/base/dists/pareto-type1/logpdf from relative-tolerance testing to ULP (units in the last place) difference testing, per the tracking issue.
  • Replaces the delta/tol (EPS-based) comparisons in test/test.logpdf.js, test/test.native.js, and test/test.factory.js with t.strictEqual( isAlmostSameValue( y, expected[ i ], 1 ), true, 'returns expected value' ).
  • The minimum ULP bound (1) was determined by measuring the actual ULP difference between the computed and expected values across all three fixture sets (large_alpha, large_beta, both_large); the measured maximum ULP difference was 0 (exact matches) for the JavaScript, factory, and native implementations, so 1 is used as the tightest bound with a minimal safety margin. Verified deterministic across two full test runs, including the native addon (built locally for verification).
  • No other tests, behavior, or files were changed.

Related Issues

Does this pull request have any related issues?

This pull request has the following related issues:

Questions

Any questions for reviewers of this pull request?

No.

Other

Any other information relevant to this pull request? This may include screenshots, references, and/or implementation notes.

No.

Checklist

Please ensure the following tasks are completed before submitting this pull request.

AI Assistance

When authoring the changes proposed in this PR, did you use any kind of AI assistance?

  • Yes
  • No

If you answered "yes" above, how did you use AI assistance?

  • Code generation (e.g., when writing an implementation or fixing a bug)
  • Test/benchmark generation
  • Documentation (including examples)
  • Research and understanding

Disclosure

If you answered "yes" to using AI assistance, please provide a short disclosure indicating how you used AI assistance. This helps reviewers determine how much scrutiny to apply when reviewing your contribution. Example disclosures: "This PR was written primarily by Claude Code." or "I consulted ChatGPT to understand the codebase, but the proposed changes were fully authored manually by myself.".

This PR was written primarily by Claude Code, which selected the candidate package, studied prior-art conversions referenced in #11352, applied the isAlmostSameValue migration, and measured the minimum ULP bound against the fixtures.


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Generated by Claude Code

@stdlib-bot stdlib-bot added Statistics Issue or pull request related to statistical functionality. Good First PR A pull request resolving a Good First Issue. labels Aug 31, 2026
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Coverage Report

Package Statements Branches Functions Lines
stats/base/dists/pareto-type1/logpdf $\\color{green}339/339$
$\\color{green}+100.00\\%$
$\\color{green}25/25$
$\\color{green}+100.00\\%$
$\\color{green}4/4$
$\\color{green}+100.00\\%$
$\\color{green}339/339$
$\\color{green}+100.00\\%$

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

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