From stefano.iacus@unimi.it  Mon Jan  7 16:10:17 2002
From: stefano.iacus@unimi.it (Stefano Iacus)
Date: Mon, 7 Jan 2002 17:10:17 +0100
Subject: [Rd] quadprog
Message-ID: <0A6D4C0A-0389-11D6-8E49-003065CC4CB8@unimi.it>

Hy,
I have to solve the following minimization problem on x

Q(x) = 1/2 x' A x + x'b

where Q is a quadratic form and x is in the simplex (x_i>=0, sum_i x_i = 
1, i=1,...,n), A pos. def. and b a negative vector.

I have tried with quadprog routines but it gives me solutions of the form
x* = (...,1,..)
where the dots "." are zeroes "0".

the toolbox optim/quadprog in Matlab lead to the same results as 
R+quaprog package (they use the "same" qld algorithm).

Are there any more efficient methods based on lagrange multipliers + 
standard simplex minimization ? I think that the qld algorithm is rather 
general and then not efficient for my specific case.

Any idea or reference ?

Stefano








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[Rd] quadprog
Stefano Iacus