kernel_reg: Kernel Regression function

In rbbnp: A Bias Bound Approach to Non-Parametric Inference

Kernel Regression function

Description

Kernel Regression function

Usage

kernel_reg(X, Y, x, h, kernel_func)

Arguments

X	A numerical vector representing the sample data of variable X.
Y	A numerical vector representing the sample data of variable Y.
x	The point at which the regression function is to be estimated.
h	A bandwidth parameter that determines the weight assigned to each observation in X.
kernel_func	A function that computes the weight of each observation based on its distance to x.

Value

Returns a scalar representing the estimated value of the regression function at the point x.

rbbnp documentation built on June 8, 2025, 10:46 a.m.