[R] regression problem

[Patrick Burns]

The function has a "coefsum" argument but never uses it.
The objective is supposed to be:

               sum((y - x %*% coef)^2) + abs(sum(coef) - coefsum) * penalty

Patrick Burns wrote:

> Assuming that you want to estimate via least squares, you can
> do something like this:
>
> reg.coefsum <- function(x, y, start=coef(lm.fit(x, y)), coefsum=0, 
> penalty=1000) {
>        subfun.objective <- function(coef){
>                sum((y - x %*% coef)^2) + abs(sum(coef)) * penalty
>        }
>        opt <- optim(start, subfun.objective, method='BFGS')
>        ans <- list(coefficients=opt$par)
>        ans
> }
>
> You can enhance the return value and make other improvements,
> like check that the coefficient sum is accurate enough for you.
>
> Patrick Burns
>
> Burns Statistics
> patrick at burns-stat.com
> +44 (0)20 8525 0696
> http://www.burns-stat.com
> (home of S Poetry and "A Guide for the Unwilling S User")
>
> pnick at virgilio.it wrote:
>
>> i need to know how to estimate a linear regression whose coefficients 
>> sum
>> to zero
>>
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>
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