[R] R-square prob is not calculated by randomization in lmPerm::lmp
Cade, Brian
cadeb at usgs.gov
Tue Sep 6 17:00:19 CEST 2016
For a linear model without an intercept term as in this example, neither
the usual permutation scheme for testing Ho: B1 = 0 nor usual definition of
R-squared apply. So you need to check what the developer of this code
chose to do. If I'm recalling correctly, in a linear model with an
intercept term the permutation test for Ho: B1 = B2 = ... Bp = 0 (i.e., all
coefficients other than the intercept = 0) is equivalent to a permutation
test for Ho: R-squared = 0.
Brian
Brian S. Cade, PhD
U. S. Geological Survey
Fort Collins Science Center
2150 Centre Ave., Bldg. C
Fort Collins, CO 80526-8818
email: cadeb at usgs.gov <brian_cade at usgs.gov>
tel: 970 226-9326
On Tue, Sep 6, 2016 at 8:35 AM, Jeff Newmiller <jdnewmil at dcn.davis.ca.us>
wrote:
> That is contributed code. It could do anything the author felt like. I
> recommend reading the source code.
> --
> Sent from my phone. Please excuse my brevity.
>
> On September 5, 2016 11:52:15 PM PDT, Agustin Lobo <aloboaleu at gmail.com>
> wrote:
> >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
>
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