Nonlinear (Nonsuperposable) Methods for Smoothing Data
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Summary¶
Presents Tukey's early formulation of nonlinear, nonsuperposable smoothing methods for data sequences, helping establish median-style smoothers as robust alternatives to linear averaging when outliers or sharp features are important. The note became a foundational citation for later median filters, rank-order filters, and LULU smoothing theory.
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