[R] multivariate nonparametric regression with e >= 0
Maciej Kalisiak
mac at dgp.toronto.edu
Thu Nov 3 20:22:51 CET 2005
Hello all,
I'm a relatively new user of R, having mostly used it only for plotting so
far. I'm also not very familiar with regression methods, hence forgive my
greenness on the topic.
What I want to do in R is multivariate nonparametric regression, with a slight
hitch. From my experimental data I have a multitude of samples whose values
approximate a function `f' that is defined over a 5D space (i.e., f: R^5->R).
The values of the collected samples, call these `y', approximate `f', but due
to the process by which they are collected, they always over-estimate (i.e., y
= f + e, e >= 0). The distribution of the error `e' can likely be modelled
using the positive half of the normal distribution.
Naturally I'm trying to obtain a smooth and relatively faithful approximation
of `f' using the collected samples `y'. What would be the most fruitful
approach in R to doing this? Even suggestions on which package/function to
use would be tremendously helpful, as I don't yet know what their
strengths/weaknesses are.
Also, I would consider parametric regression as well, but in the general case
I don't think I can assume/guess for my data at what the appropriate
parametric basis functions should be...
--
Maciej Kalisiak <mac at dgp.toronto.edu>
http://www.dgp.toronto.edu/~mac/
More information about the R-help
mailing list