Any reason why the R-square prob is not calculated by randomization in
lmPerm::lmp? The help pages states "Either permutation test p-values
or the usual F-test p-values will be output", but I always get the F
test for R-square as with lm():
require(lmPerm)
x <- 1:1000
set.seed(1000)
y1 <- x*2+runif(1000,-100,100)
dat <- data.frame(x =x,y=y1)
summary(lmp(y~x, data=dat,center=FALSE,perm="Prob"))
[1] "Settings: unique SS "
Call:
lmp(formula = y ~ x, data = dat, center = FALSE)
Residuals:
Min 1Q Median 3Q Max
-100.431 -48.645 2.843 48.640 101.800
Coefficients:
Estimate Iter Pr(Prob)
x 1.993 5000 <2e-16 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 57.3 on 998 degrees of freedom
Multiple R-Squared: 0.9902, Adjusted R-squared: 0.9902
F-statistic: 1.009e+05 on 1 and 998 DF, p-value: < 2.2e-16
--
Agustin Lobo
aloboa...@gmail.com
______________________________________________
R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
