Hi all at the R-teaching mailing list,
I am currently preparing my first R-based regression course. Along
this way I encountered the following problem:
I want to simulate multivariate data that has some specific predefined
attributes. For example I want to produce a Predictor-matrix (X)
and a response-vector (y) that will yield a given vector of regression
coefficients (b) and a given R2 when I perform a multivariate linear
Regression
on the dataset. This would be best described by the well known equation
y=X*b+e.
In some next step I also want to simulate polynomic relationships, but I
think that should work not very different.
I already searched the web and found some hints, but no clear answer.
There is a pdf out there from John H. Walker (Teaching Regression with
simulation)
which does however not discuss this special topic. I also have a Paper
from K.Baumann 'Chance Correlation in variable subset regression:
Influence of the objective function, selection mechanism and Ensemble
averaging' QCS, 2005. There an 'Autoregressive process' is used to
simulate such data.
Now my question is:
Is it really that difficult to simulate such data? Is there perhaps a
package in R facilitating at least parts of this work?
Thanks in advance for the help,
Markus
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