Library: | spatial |
See also: | SPKRsurfgls SPKRexpcov SPKRgaucov SPKRsphercov SPKRtrmat SPKRprmat SPKRsemat SPKRcorrelogram SPKRvariogram SPKRmultcontours |
Quantlet: | SPKRsurfls | |
Description: | fits a trend surface, i.e., a polynomial regression surface, by least squares |
Usage: | res = SPKRsurfls(np, xmat) | |
Input: | ||
np | scalar, degree of the polynomial surface, an integer in the range 0..6 | |
xmat | n x 3 matrix of locations (x_i, y_i) [columns 1 & 2] and observations z_i [column 3] | |
Output: | ||
res | list, consisting of components x, y, z, np, f, r, beta, wz, minx, maxx and type: | |
res.x | n x 1 vector, same as xmat[,1] | |
res.y | n x 1 vector, same as xmat[,2] | |
res.z | n x 1 vector, same as xmat[,3] | |
res.np | scalar, same as input value np | |
res.f | matrix, internal use only | |
res.r | matrix, internal use only | |
res.beta | matrix, containing (np + 1)(np + 2) / 2 coefficients | |
res.wz | matrix, internal use only | |
res.minx | 1 x 3 vector, minimum of columns of xmat | |
res.maxx | 1 x 3 vector, maximum of columns of xmat | |
res.type | string, "trls" |
; loads the spatial statistics library library("spatial") ; reads a spatial data set topo = read("topo.dat") ; calculates a polynomial regression surface of order 2 myres = SPKRsurfls(2, topo) myres.minx myres.maxx
A list consisting of input parameters, intermediate and final results of a polynomial regression surface. This list will be used in other spatial statistics quantlets such as SPKRtrmat, SPKRcorrelogram, or SPKRvariogram. Contents of minx [1,] 0.2 0 690 Contents of maxx [1,] 6.3 6.2 960