LOESS: Multivariate smoothing by moving least squares. LOESS is a method for smoothing scattered data in one or more variables by local fitting of linear or quadratic models with a neighborhood weighting that is moved across the domain. A program is available to accelerate the basic method by building a k-d tree, fitting only at vertices, and extending by cubic Hermite blending.