test: migrate stats/base/dists/gamma/skewness to ULP-based assertions

[kgryte]

Resolves a part of #11352.

Description

What is the purpose of this pull request?

This pull request:

• migrates the tests for stats/base/dists/gamma/skewness from relative tolerance testing to ULP difference testing, per [RFC]: Migrate math/base/special packages from relative tolerance testing to ULP difference testing (tracking issue) #11352.
• replaces the delta/tol (2.0 * EPS * abs( expected[i] )) comparisons in test/test.js and test/test.native.js with t.strictEqual( isAlmostSameValue( y, expected[ i ], 0 ), true, 'returns expected value' );, adding the @stdlib/assert/is-almost-same-value import and removing the now unused @stdlib/math/base/special/abs and @stdlib/constants/float64/eps imports.

Final ULP constant: 0 for both test/test.js and test/test.native.js.

This is the measured minimum. Starting from a high bound and tightening, the maximum ULP difference over the full 200-case Julia fixture set (test/fixtures/julia/data.json) is 0 for both the JavaScript and native implementations: all 200 cases are bit-for-bit exact, so the bound cannot be tightened further. The suite was run twice at the final bound with identical results, and the native addon was compiled locally so that test/test.native.js actually executed rather than being skipped:

• test/test.js: 214 passing, 0 failing
• test/test.native.js: 214 passing, 0 failing

This matches the sibling package stats/base/dists/gamma/kurtosis, which also uses a bound of 0.

Only the two test files are changed.

Related Issues

Does this pull request have any related issues?

This pull request has the following related issues:

• [RFC]: Migrate math/base/special packages from relative tolerance testing to ULP difference testing (tracking issue) #11352

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.

The JavaScript and native implementations agree exactly here, so the same ULP bound applies to both files.

Checklist

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

• Read, understood, and followed the contributing guidelines.

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

This PR was authored by Claude Code running as an automated task. The tolerance-to-ULP conversion, the search for the minimum ULP bound, and the local test/lint verification were all performed by Claude Code.

---

@stdlib-js/reviewers

🤖 Generated with Claude Code

https://claude.ai/code/session_01F98j9sSCh3XzoRpXNvsPc6

---

Generated by Claude Code

[stdlib-bot]

Coverage Report

Package	Statements	Branches	Functions	Lines
stats/base/dists/gamma/skewness	$\\color{green}196/196$ $\\color{green}+100.00\\%$	$\\color{green}10/10$ $\\color{green}+100.00\\%$	$\\color{green}2/2$ $\\color{green}+100.00\\%$	$\\color{green}196/196$ $\\color{green}+100.00\\%$

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

[Planeshifter]

⚠️ Issue Reference Review

An automated check found potentially unrelated issue/PR references in this PR:

Reference	Assessment	Reasoning
#11352	suspicious	Issue #11352 is an RFC explicitly scoped to migrating math/base/special packages from relative-tolerance testing to ULP-difference testing, but this PR modifies tests in stats/base/dists/gamma/skewness, a different package tree not covered by that RFC's stated scope.

Why this matters: GitHub automatically closes issues referenced with
closing keywords (Resolves, Closes, Fixes) when the PR is merged. Incorrect
references can accidentally close unrelated issues.

What to do:

• If the reference is correct, no action needed. This check may produce
  false positives.
• If the reference is incorrect, please update your PR description.

This assessment was generated by an AI model and is informational only.

---

Generated by Claude Code