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: | myres = 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, type -- | |
x | n x 1 - same as xmat[,1] | |
y | n x 1 - same as xmat[,2] | |
z | n x 1 - same as xmat[,3] | |
np | scalar - same as input value np | |
f | matrix - internal use only | |
r | matrix - internal use only | |
beta | matrix - (np + 1)(np + 2) / 2 coefficients | |
wz | matrix - internal use only | |
minx | 1 x 3 - minimum of columns of xmat | |
maxx | 1 x 3 - maximum of columns of xmat | |
type | string - "trls" |
; load the spatial statistics library library ("spatial") ; read a spatial data set topo = read("topo.dat") ; calculate a polynomial regression surface of order 2 myres = SPKRsurfls (2, topo)
A list consisting of input parameters, intermediate results, and final results of a polynomial regression surface. This list will be used in other spatial statistics quantlets such as SPKRtrmat, SPKRcorrelogram, or SPKRvariogram.
Library: | spatial |
See also: | SPKRsurfgls SPKRexpcov SPKRgaucov SPKRsphercov SPKRtrmat SPKRprmat SPKRsemat SPKRcorrelogram SPKRvariogram SPKRmultcontours |