feat: add stats/incr/nanrmse

[wilmerdooley]

Description

This pull request adds a new package to the stats/incr/* namespace: @stdlib/stats/incr/nanrmse, resolving #5621.

The package incrementally computes the root mean squared error (RMSE), ignoring NaN values. Following the pattern of @stdlib/stats/incr/nansum (and the existing @stdlib/stats/incr/nanmse), the accumulator is a thin wrapper around @stdlib/stats/incr/rmse: when either input value is NaN (or no arguments are provided), the value is skipped and the current RMSE is returned; otherwise the value is forwarded to the underlying incrrmse accumulator.

Included (package directory only, consistent with the existing nanmse/nanmmse/nanvariance additions):

• lib/main.js, lib/index.js
• test/test.js
• benchmark/benchmark.js
• examples/index.js
• docs/repl.txt, docs/types/index.d.ts, docs/types/test.ts, docs/img/equation_root_mean_squared_error.svg, README.md

Related Issues

Resolves #5621.

Questions

I implemented this as a package-only addition, matching the existing @stdlib/stats/incr/nanmse, @stdlib/stats/incr/nanmmse, and @stdlib/stats/incr/nanvariance packages, which do not modify the namespace. Should the new package also be registered in the @stdlib/stats/incr namespace index and the @stdlib/namespace alias tables, or is that registration handled separately by the maintainers? Happy to add it in this PR if that is preferred.

Other

Verified locally against the project's own tooling:

• ESLint (per-category configs: src, test, examples, benchmark): 0 problems
• TypeScript declarations, Markdown (README), EditorConfig, license headers: all pass
• Unit tests: 17/17 assertions passing
• Coverage: 100% statements, branches, functions, and lines (istanbul)

Checklist

• Read, understood, and followed the contributing guidelines.
• Added/updated tests, benchmarks, examples, and documentation.

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 with assistance from Claude Code. The implementation, tests, documentation, and benchmarks were generated with AI assistance and then reviewed for correctness against the expected RMSE behavior and adapted to follow the conventions of the existing @stdlib/stats/incr/rmse and @stdlib/stats/incr/nanmse packages.