# Kernel smoother

## Statistical technique / From Wikipedia, the free encyclopedia

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A **kernel smoother** is a statistical technique to estimate a real valued function $f:\mathbb {R} ^{p}\to \mathbb {R}$ as the weighted average of neighboring observed data. The weight is defined by the *kernel*, such that closer points are given higher weights. The estimated function is smooth, and the level of smoothness is set by a single parameter.
Kernel smoothing is a type of weighted moving average.