[R] interpretation of RCS 'coefs' and 'knots'

[Kingsford Jones]

Perhaps functional data analysis would be of interest.  See, for
example, package fda.

Kingsford

On Fri, Oct 23, 2009 at 4:46 PM, Dylan Beaudette
<debeaudette at ucdavis.edu> wrote:
> Hi,
>
> 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?
>
> Cheers,
> Dylan
>
> --
> Dylan Beaudette
> Soil Resource Laboratory
> http://casoilresource.lawr.ucdavis.edu/
> University of California at Davis
> 530.754.7341
>
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