Hi there,
I use the surf.gls() function to fit a variable measured over a surface. When I
plot the predicted surface, there are local minima/maxima in almost every
coordinate where data were measured, which seems aberrant. For instance:
?? x <-
c(343,293,343,243,293,343,443,543,593,243,293,343,393,443,493,543,593,143,193,243,293,343,393,443,
493,543,593,193,243,293,343,543,593,643,93,193,243,293,343,393,443,493,543,43,93,143,193,243,293,
343,393,443,493,543,593,193,243,293,343,393,443,493,543,593,643,143,193,243,293,343,443,543,593,
643,693,143,293,393,443,493,543,593,643,243,293,343,393,493,593,643,243,343,393,243,343,393,343)
y <-
c(720,670,670,620,620,620,620,620,620,570,570,570,570,570,570,570,570,520,520,520,520,520,520,520,
520,520,520,470,470,470,470,470,470,470,420,420,420,420,420,420,420,420,420,370,370,370,370,370,370,
370,370,370,370,370,370,320,320,320,320,320,320,320,320,320,320,270,270,270,270,270,270,270,270,270,
270,220,220,220,220,220,220,220,220,170,170,170,170,170,170,170,120,120,120,70,70,70,20)
z <-
c(0.66,0.66,0.66,0.66,0.66,0.66,0.67,0.66,0.66,0.66,0.66,0.66,0.67,0.67,0.66,0.66,0.66,0.66,0.66,0.66,0.66,
0.69,0.67,0.67,0.66,0.66,0.66,0.67,0.67,0.66,0.69,0.66,0.66,0.66,0.66,0.67,0.67,0.67,0.78,0.74,0.74,0.68,
0.68,0.66,0.66,0.66,0.66,0.66,0.72,0.72,0.83,0.70,0.66,0.66,0.66,0.67,0.67,0.67,0.67,0.74,0.70,0.70,0.66,
0.66,0.66,0.67,0.67,0.67,0.67,0.67,0.67,0.66,0.66,0.66,0.66,0.67,0.67,0.66,0.67,0.67,0.66,0.66,0.66,0.66,
0.66,0.66,0.66,0.67,0.66,0.66,0.66,0.66,0.66,0.66,0.66,0.66,0.66)
dat <- data.frame(x, y, z)
kr <- surf.gls(2, expcov, dat, d = 0.7, nx = 1000)
prsurf <- prmat(kr, min(x), max(x), min(y), max(y), 500)
image(prsurf, col = rainbow(1000))
One can see that local maxima/minima are found where data were measured:
points(x, y, cex = 2)
The surface I obtain can be visualised here:
http://nsa34.casimages.com/img/2013/03/16/130316115621267122.png
Thanks for your help,
Florent Pantin
John Innes Centre
Norwich
UK
