Fast Computation of Auxiliary Quantities in Local Polynomial Regression
AbstractWe investigate the extension of binning methodology to fast computation of several auxiliary quantities that arise in local polynomial smoothing. Examples include degrees of freedom measures, cross-validation functions, variance estimates and exact measures of error. It is shown that the computational effort required for such approximations is of the same order of magnitude as that required for a binned local polynomial smooth.
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Bibliographic InfoPaper provided by Australian Graduate School of Management in its series Statistics Working Paper with number 95009.
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