| trls.influence {spatial} | R Documentation |
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.
trls.influence(object)
plot(x, border = "red", col = NA, pch = 4, cex = 0.6,
add = FALSE, div = 8, ...)
object, x |
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
|
border, col, pch, cex, ... |
additional graphical parameters |
r |
raw residuals as given by residuals.trls
|
hii |
diagonal elements of the Hat matrix |
stresid |
standardised residuals |
Di |
Cook's statistic |
trls.influence returns a list with:
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.
surf.ls, influence.measures, plot.lm
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)