feat: add stats/incr/nanmidrange

[sanki92]

Add stats/incr/nanmidrange

Resolves #5578.

Description

What is the purpose of this pull request?

This pull request:

• Adds @stdlib/stats/incr/nanmidrange package for incrementally computing mid-range while ignoring NaN values
• Implements the accumulator following the same pattern as other nan* packages in the stats/incr namespace
• Uses a thin wrapper around @stdlib/stats/incr/midrange that skips NaN inputs

Related Issues

Does this pull request have any related issues?

This pull request has the following related issues:

• [RFC]: add stats/incr/nanmidrange #5578 (parent tracking issue: [RFC]: add incremental accumulators for handling NaN values in stats/incr/* (tracking issue) #5966)

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 implementation follows the established pattern from @stdlib/stats/incr/nanmin and @stdlib/stats/incr/nansum. The package wraps the existing incrmidrange accumulator and filters out NaN values before passing them through.

All standard package files are included:

• Main implementation (lib/)
• Comprehensive tests with NaN handling scenarios
• Example demonstrating usage with NaN values
• Benchmark suite
• TypeScript definitions
• REPL documentation

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

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.".

Used AI to understand the codebase structure and identify the appropriate pattern to follow from existing nan* packages. The implementation was manually written by adapting the midrange package with the NaN-handling wrapper pattern observed in nanmin and nansum.

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