
Dear R users,
I'd like to known your opinion about a problem with anova.lmRob() of "Robust" package that occurs when I run a lmRob() regression on my dataset.
I check my univariate model by single object anova as anova(lmRob(y~x)).
If I compare my model with the null model (y~1), I must obtain the same results, 
but not for my data.
Is it possible?

My example:

x<-c(rep(0,8),rep(1,8),rep(2,7))
y<-c(1,0.6,-0.8,0.7,1.6,-0.2,-1.2,-3.8,-1.8,-2.6,-1.7,-2.1,-0.3,-1.4,1.4,-0.3,-0.3,0.5,0.4,-0.9,-1.6,0.4,0.4)
library(robust)
lmR<-lmRob(y~factor(x))
anova(lmR)
lmR0<-lmRob(y~1)
anova(lmR,lmR0)

If I run the code omitting the factor() (then treating "x" as continuous), the results are the same..


What is the explanation of these different results?

Thanks in advance!

Massimo 


Massimo FenatiDVM - Specialized in Animal Health and HusbandryVia Mameli 5 - 35040 Boara Pisani (PD)Italye-mail: m.fenati@libero.it 

	[[alternative HTML version deleted]]

