LOESS(x;d;s;l)
or LO(x;d;s;l)
fits a locally weighted regression of order l
(= 1 for linear, 2 for quadratic) with approximately d
degrees of freedom or using smoothing parameter s
(regression models only): x
is a variate for univariate smoothing, or a pointer to up to four variates for multivariate smoothing; when x
is a variate l
is a scalar, when x
is a pointer it is either a scalar or a variate with an element for each variate in the pointer (regression and generalized linear models only).
LOESS
Updated on December 4, 2017