Lwls2DDeriv: Two dimensional local linear kernel smoother to target... In fdapace: Functional Data Analysis and Empirical Dynamics

Description

Two dimensional local weighted least squares smoother. Only a local linear smoother for estimating the original curve is available (no higher order)

Usage

 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 Lwls2DDeriv( bw, kern = "epan", xin, yin, win = NULL, xout1 = NULL, xout2 = NULL, xout = NULL, npoly = 1L, nder1 = 0L, nder2 = 0L, subset = NULL, crosscov = TRUE, method = "sort2" )

Arguments

 bw A scalar or a vector of length 2 specifying the bandwidth. kern Kernel used: 'gauss', 'rect', 'gausvar', 'epan' (default), 'quar'. xin An n by 2 data frame or matrix of x-coordinate. yin A vector of y-coordinate. win A vector of weights on the observations. xout1 a p1-vector of first output coordinate grid. Defaults to the input gridpoints if left unspecified. xout2 a p2-vector of second output coordinate grid. Defaults to the input gridpoints if left unspecified. xout alternative to xout1 and xout2. A matrix of p by 2 specifying the output points (may be inefficient if the size of xout is small). npoly The degree of polynomials (include all x^a y^b terms where a + b <= npoly) nder1 Order of derivative in the first direction nder2 Order of derivative in the second direction subset a vector with the indices of x-/y-/w-in to be used (Default: NULL) crosscov using function for cross-covariance estimation (Default: TRUE) method should one try to sort the values xin and yin before using the lwls smoother? if yes ('sort2' - default for non-Gaussian kernels), if no ('plain' - fully stable; de)

Value

a p1 by p2 matrix of fitted values if xout is not specified. Otherwise a vector of length p corresponding to the rows of xout.

fdapace documentation built on Nov. 23, 2021, 1:06 a.m.