![]() They address situations in which the classical procedures do not perform well or cannot be effectively applied without undue labor. LOESS and LOWESS thus build on "classical" methods, such as linear and nonlinear least squares regression. In some fields, LOESS is known and commonly referred to as Savitzky–Golay filter (proposed 15 years before LOESS). They are two strongly related non-parametric regression methods that combine multiple regression models in a k-nearest-neighbor-based meta-model. Its most common methods, initially developed for scatterplot smoothing, are LOESS ( locally estimated scatterplot smoothing) and LOWESS ( locally weighted scatterplot smoothing), both pronounced / ˈ l oʊ ɛ s/. Local regression or local polynomial regression, also known as moving regression, is a generalization of the moving average and polynomial regression. The LOESS curve approximates the original sine wave. LOESS curve fitted to a population sampled from a sine wave with uniform noise added. ( June 2011) ( Learn how and when to remove this template message) Please help to improve this article by introducing more precise citations. This article includes a list of general references, but it remains largely unverified because it lacks sufficient corresponding inline citations.
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