Module smoothing 

Smoothing functions for functional data.

This module provides kernel-based smoothing methods including Nadaraya-Watson, local linear, and local polynomial regression.

Structs

KnnCvResult

Result of kNN k-selection by cross-validation.

OptimBandwidthResult

Result of bandwidth optimization.

Enums

CvCriterion

CV criterion type for bandwidth selection.

Functions

cv_smoother

LOO-CV score for a kernel smoother (R’s CV.S).

gcv_smoother

GCV score for a kernel smoother (R’s GCV.S).

knn_gcv

Global LOO-CV for kNN k selection (R’s knn.gcv).

knn_lcv

Local (per-observation) LOO-CV for kNN k selection (R’s knn.lcv).

knn_smoother

k-Nearest Neighbors smoother.

local_linear

Local linear regression smoother.

local_polynomial

Local polynomial regression smoother.

nadaraya_watson

Nadaraya-Watson kernel smoother.

optim_bandwidth

Bandwidth optimizer for kernel smoothers (R’s optim.np).

smoothing_matrix_nw

Compute smoothing matrix for Nadaraya-Watson.

solve_gaussian_pub

Solve a linear system Ax = b via Gaussian elimination with partial pivoting.