[R] interpretation of RCS 'coefs' and 'knots'
kingsfordjones at gmail.com
Sat Oct 24 17:43:27 CEST 2009
Perhaps functional data analysis would be of interest. See, for
example, package fda.
On Fri, Oct 23, 2009 at 4:46 PM, Dylan Beaudette
<debeaudette at ucdavis.edu> wrote:
> I have fit a series of ols() models, by group, in this manner:
> l <- ols(y ~ rcs(x, 4))
> ... where the series of 'x' values in each group is the same, however knots
> are not always identical between groups. The result is a table of 'coefs'
> derived from the ols objects, by group:
> group Intercept top top' top''
> 1 6.864 0.01 2.241 -2.65
> 2 6.836 0.047 -0.556 0.606
> 3 5.877 -0.019 0.084 -0.175
> 4 6.021 -0.003 0.121 -0.128
> 5 7.164 0.014 0.031 -0.096
> I would like to describe groups of relationships, based on the coefficients,
> however I am not sure if they are directly comparable. In addition, I would
> like to regress these coefs on another set of variables, with the aim of
> predicting a series of RCS coefficients along external gradients. In essence,
> I am hoping to use RCS coefficients to summarize y ~ rcs(x), in a way that
> can then me modeled like this: [y ~ rcs(x)] ~ z.
> Is this interpretation of RCS coefficients even possible? If not, would
> forcing knot locations make it a possibility? Or, would modeling both knots
> and RCS coefs with external variables lead to sensible predictions?
> Dylan Beaudette
> Soil Resource Laboratory
> University of California at Davis
> R-help at r-project.org mailing list
> PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.
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