In a lm() model a significant intercept means that the line passes above or
below the intercept (x=0, y=0). A significant predictor means that the slope is
not zero. More generally the significant predictor means that the predictor
has some influence on the predicted. With nlme() the relationsh
Yikes!
This list is for help on R *programming*, not statistics per se,
although these do sometimes intersect. However, your query strikes me
as a request for a kind of statistical tutorial, which is OT here.
Just so you are aware...
R has a special interest group (SIG) for phylgenetics at
https:
Dear all
I have undertaken some phylogenetic and non-phylogenetic regressions with
gls() in nlme with single preictor variables. A p value is associated with
the intercept (upper p value) and another with the predictor variable
(lower). Which p value is important? What does it mean if the intercep
Thanks, Martin. This is very helpful.
On Tue, 16 Jul 2024 at 14:52, Martin Maechler
wrote:
> > Anupam Tyagi
> > on Tue, 9 Jul 2024 16:16:43 +0530 writes:
>
> > How can I do automatic knot selection while fitting piecewise linear
> > splines to two variables x and y? Which p
> Anupam Tyagi
> on Tue, 9 Jul 2024 16:16:43 +0530 writes:
> How can I do automatic knot selection while fitting piecewise linear
> splines to two variables x and y? Which package to use to do it simply? I
> also want to visualize the splines (and the scatter plot) with a
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