I have a set of values of r squared from different robust estimators. The r squared values fall not fall from each other. I want to test if they are significantly different from each other. Is it possible? If yes, what test should i use? Should i use ANOVA? (i doubt myself for using ANOVA since my values are not from group means). Thank you very much
btw, here are the estimators i used and took the r squared values for each estimator
#estimation
OLS<-lm(dv~iv)
Huber1<-rlm(dv~iv,maxit=50)
Huber2<-rlm(dv~iv,scale.est="proposal 2")
Tukey<- rlm(dv~iv,psi="psi.bisquare")
LTS<-ltsReg(dv~iv)
S<-lqs(dv~iv,method="S")
MM<-rlm(dv~iv,method="MM", psi=psi.bisquare, maxit=50)
EDIT: The r squared values (which i computed manually) are close to each other. (i.e 0.40567,0.41003,0.40809 ... ) and i want to be sure that they are significantly different from each other.
the data i simulated has X~N(0,1).