trls.influence {spatial}R Documentation

Regression diagnostics for trend surfaces

Description

This function provides the basic quantities which are used in forming a variety of diagnostics for checking the quality of regression fits for trend surfaces calculated by surf.ls.

Usage

trls.influence(object)
plot(object, border = 1, col = NA, pch = 4, cex = 0.6, 
          add = FALSE, div = 8)

Arguments

object Fitted trend surface model from surf.ls
div scaling factor for influence circle radii in plot.trls
add add influence plot to existing graphics if TRUE
r raw residuals as given by residuals.trls
hii diagonal elements of the Hat matrix
stresid standardised residuals
Di Cook's statistic

Value

trls.influence returns a list with:

References

Unwin, D. J., Wrigley, N. (1987) Towards a general-theory of control point distribution effects in trend surface models. Computers and Geosciences, 13, 351–355.

See Also

surf.ls, influence.measures, plot.lm

Examples

library(MASS)
data(topo)
topo2 <- surf.ls(2, topo)
infl.topo2 <- trls.influence(topo2)
cand <- as.data.frame(infl.topo2)[abs(infl.topo2$stresid) > 1.5,]
cand
cand.xy <- topo[as.integer(rownames(cand)), c("x", "y")]
trsurf <- trmat(topo2, 0, 6.5, 0, 6.5, 50)
eqscplot(trsurf, type="n")
#under S need to choose appropriate colour numbers
contour(trsurf, add=TRUE, col="grey")
plot(topo2, add=TRUE, div=3)
points(cand.xy, pch=16, col="orange")
text(cand.xy, labels=rownames(cand.xy), pos=4, offset=0.5)