questions about anova
On Sat, 28 Feb 2004, Carlos Henrique Grohmann wrote:
Hello all, I have two questions about anova (one is probably VERY basic...)
About surf.ls() in the spatial package, and documented in Venables & Ripley Modern Applied Statistics with S ...
1 - when one asks for a summary of a trend surface created with surf.ls, he/she gets:
summary(g3r)
Analysis of Variance Table
Model: surf.ls(np = 3, x = gradiente$east, y = gradiente$north, z =
gradiente$num1)
Sum Sq Df Mean Sq F value Pr(>F)
Regression 215.7182 9 23.968693976 2686.508 < 2.22e-16
Deviation 480.1218 53814 0.008921876
Total 695.8401 53823
Multiple R-Squared: 0.31, Adjusted R-squared: 0.3099
AIC: (df = 53814) -146390.9
Fitted:
Min 1Q Median 3Q Max
0.007852 0.075619 0.100498 0.139042 0.338186
Residuals:
Min 1Q Median 3Q Max
-0.29758 -0.04418 -0.01411 0.02536 0.51484
So, what's the meaning of the "Pr(>F)?
Roughly here that, if the model assumptions are met, that the reduction of sum of squares from total to deviation could have occurred at random, and that the reduction represented by the cubic trend surface does make a difference. Note that the observations are probably not independent, so the assumptions may not be met, and with the number of observations you have here, almost anything will appear to be significant.
2 - I have six trend surfaces, and I like to make a anova for the significance of increasing the degree of polynomial (like in Davis, 1986, p.422, Statistics and data analysis in geology). is there a way I can do it automatically or should I do it manually?
See the example in help(anova.trls): anova(topo0, topo1, topo2, topo3, topo4) which compares the trend surfaces from 0 to 4th order. There are concerns about trying to fit higher-order surfaces because of co-linearity.
Thanks all.
Roger Bivand Economic Geography Section, Department of Economics, Norwegian School of Economics and Business Administration, Breiviksveien 40, N-5045 Bergen, Norway. voice: +47 55 95 93 55; fax +47 55 95 93 93 e-mail: Roger.Bivand at nhh.no