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 <debeaude...@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 > > ______________________________________________ > R-help@r-project.org 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. > ______________________________________________ R-help@r-project.org 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.
