surf.ls: Fits a Trend Surface by Least-squares

In spatial: Functions for Kriging and Point Pattern Analysis

Fits a Trend Surface by Least-squares

Description

Fits a trend surface by least-squares.

Usage

surf.ls(np, x, y, z)

Arguments

np	degree of polynomial surface
x	x coordinates or a data frame with columns x, y, z
y	y coordinates
z	z coordinates. Will supersede x$z

Value

list with components

beta	the coefficients
x
y
z	and others for internal use only.

References

Ripley, B. D. (1981) Spatial Statistics. Wiley.

Venables, W. N. and Ripley, B. D. (2002) Modern Applied Statistics with S. Fourth edition. Springer.

See Also

trmat, surf.gls

Examples

library(MASS)  # for eqscplot
data(topo, package="MASS")
topo.kr <- surf.ls(2, topo)
trsurf <- trmat(topo.kr, 0, 6.5, 0, 6.5, 50)
eqscplot(trsurf, type = "n")
contour(trsurf, add = TRUE)
points(topo)

eqscplot(trsurf, type = "n")
contour(trsurf, add = TRUE)
plot(topo.kr, add = TRUE)
title(xlab= "Circle radius proportional to Cook's influence statistic")

spatial documentation built on July 26, 2023, 5:33 p.m.