Merge branch 'dev'

lib/filters/nw/Nw.md

@@ -14,9 +14,7 @@
 | **Signature**    | [nw_signature](nw_signature.md) |
 
 - NW computes the Nadaraya-Watson kernel regression estimator with a Gaussian kernel, producing a nonparametric smooth of the price series.
-- Parameterized by `period` (default 64), `bandwidth` (default 8.0).
-- Output range: Tracks input.
-- Requires `period` bars of warmup before first valid output (IsHot = true).
+- **Similar:** [Loess](../loess/Loess.md), [SGF](../sgf/Sgf.md) | **Complementary:** Bandwidth selection via cross-validation | **Trading note:** Nadaraya-Watson kernel regression; non-parametric smoother with Gaussian kernel.
 - Validated against TA-Lib, Skender, and Tulip reference implementations where available.
 
 NW computes the Nadaraya-Watson kernel regression estimator with a Gaussian kernel, producing a nonparametric smooth of the price series. For each bar, every observation in the lookback window is weighted by a Gaussian function of its temporal distance, with the bandwidth parameter $h$ controlling the effective smoothing radius. Small $h$ tracks price tightly (low bias, high variance); large $h$ smooths heavily (high bias, low variance). This implementation is non-repainting (backward-looking only).
@@ -127,4 +125,4 @@ AVX2 dot product on contiguous double array: ~200-250 cy for N=200 vs ~1200 scal
 
 - Nadaraya, E.A. (1964). "On Estimating Regression." *Theory of Probability and Its Applications*, 9(1), 141-142.
 - Watson, G.S. (1964). "Smooth Regression Analysis." *Sankhyā: The Indian Journal of Statistics*, Series A, 26(4), 359-372.
-- Wand, M.P. & Jones, M.C. (1995). *Kernel Smoothing*. Chapman & Hall/CRC. Chapter 2: The Density Estimator.
+- Wand, M.P. & Jones, M.C. (1995). *Kernel Smoothing*. Chapman & Hall/CRC. Chapter 2: The Density Estimator.