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) ## S3 method for class 'trls': 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 
trls.influence
returns a list with components:
r 
raw residuals as given by residuals.trls

hii 
diagonal elements of the Hat matrix 
stresid 
standardised residuals 
Di 
Cook's statistic 
Unwin, D. J., Wrigley, N. (1987) Towards a generaltheory of control point distribution effects in trend surface models. Computers and Geosciences, 13, 351–355.
Venables, W. N. and Ripley, B. D. (2002) Modern Applied Statistics with S. Fourth edition. Springer.
surf.ls
, influence.measures
, plot.lm
library(MASS) # for eqscplot data(topo, package = "MASS") topo2 < surf.ls(2, topo) infl.topo2 < trls.influence(topo2) (cand < as.data.frame(infl.topo2)[abs(infl.topo2$stresid) > 1.5, ]) cand.xy < topo[as.integer(rownames(cand)), c("x", "y")] trsurf < trmat(topo2, 0, 6.5, 0, 6.5, 50) eqscplot(trsurf, type = "n") 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)