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Weighted local polynomial regression is a type of regression analysis that weights the regression equation based on the proximity of neighboring points to the point being estimated. This technique is particularly useful when the data have a non-linear relationship or when there are outliers in the data set. It works by fitting a polynomial to the data points that are closest to the point being estimated, and then weighting the equation by the distance of each point from the point being estimated. This helps to smooth out the data and improve the accuracy of the regression equation.
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