Add kernel weighting functions

[thisisamirv]

Summary

This PR adds a new module kernel_weights providing common statistical kernel functions used in local regression and kernel density estimation.

Details

• Implements five kernels:
  • tricube
  • epanechnikov
  • gaussian
  • triangular
  • quartic (biweight)
• Adds corresponding types (Tricube, Gaussian, Epanechnikov, Triangular, Quartic) implementing a new KernelFn trait.
• Allows fn(f64) -> f64 to be used directly as KernelFn.
• Includes integration and behavioral tests ensuring normalization and symmetry.
• Fully documented with Rustdoc examples and #[must_use] attributes.

Motivation

Kernel weighting functions are widely used in nonparametric statistics (LOESS, KDE, SVMs).
Adding them directly to ndarray-stats provides a reusable foundation for local regression and density estimation tools without external dependencies.

Checklist

• Tests added and passing (cargo test --test kernel_weights)
• cargo fmt and cargo clippy --all-targets -- -D warnings clean