[R] regression problem

[Patrick Burns]

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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