[R] optimization with inequalities
Peter Dalgaard
p.dalgaard at biostat.ku.dk
Mon Nov 28 17:10:19 CET 2005
Florent Bresson <f_bresson at yahoo.fr> writes:
> 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 ?
If you think the boundaries in lower=c(....) are recomputed as the
iteration progresses, you're wrong. L-BGFS-B does box constraints
only. Instead parametrize using
q1=p1+p3
q2=p1+p2+p3
q3=p3
which is easily inverted to get the p's from the q's. Then optimize as
a function of q1..q3, substituting the inversion in the expression for
func (which btw needs to be a _function_), using the relevant box
constraints.
--
O__ ---- Peter Dalgaard Øster Farimagsgade 5, Entr.B
c/ /'_ --- Dept. of Biostatistics PO Box 2099, 1014 Cph. K
(*) \(*) -- University of Copenhagen Denmark Ph: (+45) 35327918
~~~~~~~~~~ - (p.dalgaard at biostat.ku.dk) FAX: (+45) 35327907
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