feat: implement entropy for hypergeometric distribution

[24archit]

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Description

What is the purpose of this pull request?

This pull request:

• Implements the entropy function for the Hypergeometric distribution.
• Adds comprehensive documentation (README and REPL help) with mathematical formulas and usage examples.
• Adds unit tests and benchmarks for both JavaScript and C implementations.

Related Issues

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This pull request has the following related issues:

• No

Questions

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No.

Other

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• 

• Local linting passed for JavaScript and Markdown files. Cppcheck was not run locally due to missing dependencies but the code compiles successfully.

Checklist

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

• Read, understood, and followed the contributing guidelines.

AI Assistance

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• No

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• 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.".

• I used AI tools (Google Gemini) primarily for documentation support and research, including understanding the mathematical formula for hypergeometric entropy and verifying test cases and example outputs. All implementation code and final logic were written and reviewed manually by me.

---

@stdlib-js/reviewers

[kgryte]

/stdlib update-copyright-years

[kgryte]

You should update your use of whitespace here and below in order to be consistent within this package and with the rest of stdlib.

Suggested change

	function entropy(N, K, n) {
	function entropy( N, K, n ) {

[kgryte]

This approach seems to match SciPy: https://github.com/scipy/scipy/blob/v1.16.2/scipy/stats/_discrete_distns.py#L704. For more robust summation, we could consider an accumulator which isn't ordinary recursive summation (e.g., https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/incr/sum).

[kgryte]

@24archit You'll need to resolve CI failures before this PR can move forward. Thanks!

[24archit]

@kgryte Thanks for the review!

I have pushed a new commit ce6f412 that addresses your feedback:

• Native C Implementation: Implemented the entropy calculation in C (replacing the placeholder).

• JavaScript Update: Refactored lib/main.js to use @stdlib/stats/incr/sum for robust summation, as you suggested.

• Refactoring: Renamed header files from mean.h to entropy.h.

• Style: Fixed all linting and formatting errors (tabs/newlines).

The CI workflows are currently waiting for approval. Could you please approve them so the checks can run?

[kgryte]

@24archit If you follow our development guide and have properly setup your local environment, you shouldn't need to rely on CI to resolve failures. We have Git hooks which automatically run various QA tasks prior to committing and pushing.

[stdlib-bot]

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