[R] optimization with inequalities

[Gabor Grothendieck]

If I understand this correctly the variables over which
you are optimizing are p[1], p[2] and p[3] whereas x and y
are fixed and known during the optimization.  In that case its
a linear programming problem and you could use the lpSolve
library which would allow the explicit specification of the
constraints.

On 11/28/05, Florent Bresson <f_bresson at yahoo.fr> wrote:
> I have to estimate the following model for several
> group of observations :
>
>  y(1-y) = p[1]*(x^2-y) + p[2]*y*(x-1) + p[3]*(x-y)
>
> with constraints :
>  p[1]+p[3] >= 1
>  p[1]+p[2]+p[3]+1 >= 0
>  p[3] >= 0
>
> I use the following code :
>  func <- sum((y(1-y) - p[1]*(x^2-y) + p[2]*y*(x-1) +
> p[3]*(x-y))^2)
>  estim <- optim( c(1,0,0),func, method="L-BFGS-B" ,
> lower=c(1-p[3], -p[1]-p[3]-1, 0) )
>
> and for some group of observations, I observe that the
> estimated parameters don't respect the constraints,
> espacially the first. Where's the problem please ?
>
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