Two dimensional local linear kernel smoother to target derivatives.
Two dimensional local weighted least squares smoother. Only a local linear smoother for estimating the original curve is available (no higher order)
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" )
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 |
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) |
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.
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