[R] scatter3d() model.summary coefficients?
John Fox
jfox at mcmaster.ca
Sat Sep 30 00:51:28 CEST 2006
Dear Anja,
As you suggest, models in scatter3d() are fit via lm() and also mgcv().
scatter3d() rescales the three variables to fit in the unit cube; I believe
that the new version of rgl makes the rescaling unnecessary, so eventually
I'll probably rework scatter3d() to avoid it. It would be better if
?scatter3d mentioned this; I've made that change in the development version
of the package.
BTW, a nice thing about R is that the source code is there, so you can look
to see what a function does.
I hope this helps,
John
--------------------------------
John Fox
Department of Sociology
McMaster University
Hamilton, Ontario
Canada L8S 4M4
905-525-9140x23604
http://socserv.mcmaster.ca/jfox
--------------------------------
> -----Original Message-----
> From: r-help-bounces at stat.math.ethz.ch
> [mailto:r-help-bounces at stat.math.ethz.ch] On Behalf Of angela baldo
> Sent: Friday, September 29, 2006 5:23 PM
> To: r-help at stat.math.ethz.ch
> Subject: [R] scatter3d() model.summary coefficients?
>
> Hello All,
>
> I am a R newbie and am probably misinterpreting something
> really obvious...
>
> In the Rcmdr package there is a scatter3d() function that can
> fit a curve and also provide coefficients for the model. If
> I'm understanding this right, I think it's calling the lower
> level stats package function lm(), which is the part that
> actually does the curve fitting.
>
> Anyway, what has me perplexed is that the model summary from
> scatter3d() has different coefficients than the one generated
> by lm(). However, the actual surface plotted by scatter3d()
> looks like the function generated by lm().
>
> In the scatter3d() docs I didn't see anything about
> transforming the coefficients or changing them somehow -
> perhaps I have not been looking in the right place?
>
> I'm using a Linux box: 2.6.17-1.2187_FC5smp, R version 2.3.1,
> Rcmdr version 1.2-0, in case that helps.
>
> Thanks very much for any enlightenment!
>
> anja
>
>
> Here's an example of the output on the same data by both
> functions. If anyone wants the dataset, let me know:
>
> > scatter3d(samples$x1, samples$y, samples$x2, fit="linear",
> residuals=TRUE, bg="white", axis.scales=TRUE, grid=TRUE,
> ellipsoid=FALSE, xlab="x1", ylab="y", zlab="x2",
> model.summary=TRUE) $linear
>
> Call:
> lm(formula = y ~ x + z)
>
> Residuals:
> Min 1Q Median 3Q Max
> -0.096984 -0.022303 0.004758 0.029354 0.091188
>
> Coefficients:
> Estimate Std. Error t value Pr(>|t|)
> (Intercept) 0.708945 0.007005 101.20 <2e-16 ***
> x 0.278540 0.011262 24.73 <2e-16 ***
> z -0.688175 0.011605 -59.30 <2e-16 ***
> ---
> Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
>
> Residual standard error: 0.03936 on 105 degrees of freedom
> Multiple R-Squared: 0.972, Adjusted R-squared: 0.9715
> F-statistic: 1822 on 2 and 105 DF, p-value: < 2.2e-16
>
> > summary(lm(formula=samples$y~samples$x1+samples$x2))
>
> Call:
> lm(formula = samples$y ~ samples$x1 + samples$x2)
>
> Residuals:
> Min 1Q Median 3Q Max
> -7865.0 -1808.6 385.8 2380.5 7394.9
>
> Coefficients:
> Estimate Std. Error t value Pr(>|t|)
> (Intercept) 92204.502 1323.217 69.68 <2e-16 ***
> samples$x1 225.882 9.133 24.73 <2e-16 ***
> samples$x2 -558.076 9.411 -59.30 <2e-16 ***
> ---
> Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
>
> Residual standard error: 3192 on 105 degrees of freedom
> Multiple R-Squared: 0.972, Adjusted R-squared: 0.9715
> F-statistic: 1822 on 2 and 105 DF, p-value: < 2.2e-16
>
> --
> Angela M. Baldo
> Computational Biologist
> USDA, ARS
> Plant Genetic Resources Unit
> & Grape Genetics Research Unit
> New York State Agricultural Experiment Station 630 W. North
> Street Geneva, NY 14456-0462 USA
>
> voice 315 787-2413 or 607 254-9413
> fax 315 787-2339 or 607 254-9339
>
> angela.baldo at ars.usda.gov
> http://www.ars.usda.gov/NAA/Geneva
>
> ______________________________________________
> R-help at stat.math.ethz.ch mailing list
> 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.
>
More information about the R-help
mailing list