[R] Constrained regressions (suggestions welcome)

[Bos, Roger]

All,

Could anyone recommend a package that allows the user to constrain the
coefficients from a multiple regression equation?  

I tried using the  gl1ce function in lasso2, but couldn't get it to
work.  I created a contrived example to illustrate my starting point.

data(cars)
 fmla <- formula(dist ~ speed)
 gl1c.E <- gl1ce(fmla, data = cars)
 gl1c.E
 gl1c.E <- gl1ce(fmla, data = cars, link=identity())
 gl1c.E

I started with the example, but I think my data is more Gaussian than
binomial.  This returns the following errors.

>      data(cars)
>      fmla <- formula(dist ~ speed)
>      gl1c.E <- gl1ce(fmla, data = cars)
Error in family(family) : 
  link "family" not available for gaussian family; available links are
'inverse', 'log', 'identity'
> source(.trPaths[5], echo=TRUE, max.deparse.length=150)
>      gl1c.E <- gl1ce(fmla, data = cars, link=identity())
Error in identity() : argument "x" is missing, with no default

In this example I haven't even gotten to the stage of constraining the
coefficients yet because I can't get the function to work with minimal
inputs.

Thanks,

RogerRoger J. Bos, CFA
Rothschild Asset Management, Inc.
Tel     +1 (212) 405-5471
Email roger.bos at rothschild.com
1251 Avenue of the Americas, NY, NY  10020
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