RE: Gradient in FindMininum
- To: mathgroup at smc.vnet.net
- Subject: [mg24043] RE: [mg24006] Gradient in FindMininum
- From: "David Park" <djmp at earthlink.net>
- Date: Wed, 21 Jun 2000 02:20:03 -0400 (EDT)
- Sender: owner-wri-mathgroup at wolfram.com
> -----Original Message----- > From: Johannes Ludsteck [mailto:ludsteck at zew.de] To: mathgroup at smc.vnet.net > Dear MathGroup Members, > Unfortunately I got no answer when I sent the question below last > week to the mathgroup mailing list. Since I think that the problem > is not a very special one but a general problem of the way how > Mathematica treats numerical integrals in the computation of > gradients, I retry to get an answer. > I want to minimize a complicated function which contains > numerical integrals. Since the function is too complicated for a > direct demonstration, I give a simple example which makes the > structure of the problem clear: > > The (example) function to be minimized is: > f[x_] := NIntegrate[g[t], {t, -Infinity, x}] > > (g is a known function; however symbolical integration is > impossible). > > When I request numerical minimization of this function by typing > > FindMinimum[f[x],{x,1}] > > Mathematica gives me the following error message: > > FindMinimum::fmgl: Gradient {Indeterminate} is not a length 1 > list of real numbers at {x} = {1.}. > > Appearently, Mathematica is not able to find the gradient > symbolically. A simple solution would be to define f using Integrate > (without prefix N) and to wrap it with N[ ]: > > f[x_]:= N[ Integrate[g[t], {t,-Infinity, x}] ] > > However, since the function contains some hundred terms, > evaluation of the function takes several minutes. (Mathematica then > tries to find the integral symbolically before applying the numerical > integration procedure.) This makes optimization impracticable. > (the function I want to optimize has about 40 variables!). > > Are there any suggestions how to avoid computation of the gradient > manually? (minimization algorithms which don't use the gradient > are impracticable.) > I.e. how can I tell Mathematica to use the first definition > > f[x_] := NIntegrate[g[t], {t, -Infinity, x}] > > for evaluation of the function and the second > > f[x_]:= N[ Integrate[g[t], {t,-Infinity, x}] ] > > for the computation of the gradient. > > Thank you > > P.S If you want to reproduce the error message, you can use a > simple definition: > > f[x_]:= x^2 + NIntegrate[ Exp[-t^2], {t, -Infinity, x} ]. > > > > > Johannes Ludsteck > Centre for European Economic Research (ZEW) Johannes, Well, I not an expert on this, but since you received no previous answers, and I was able to find out something, I will post it. I think you have to use the proper form of FindMinimum (two starting points) when Mathematica can't calculate a symbolic derivative. For your simple example: f[x_] := x^2 + NIntegrate[ Exp[-t^2], {t, -Infinity, x} ] FindMinimum[f[x], {x, {1, 1.1}}] {0.666069, {x -> -0.419365}} Plot[f[x], {x, -3, 3}]; checks the solution. Or if your are going to do a lot of calculations on the function, you might consider calculating an InterpolationFunction approximation once and for all, and then using it in subsequent operations. Of course, you lose a little accuracy. fi = Interpolation[Table[{x, f[x]}, {x, -3, 3, 0.1}]] InterpolatingFunction[{{-3., 3.}}, "<>"] FindMinimum[fi[x], {x, {1, 2}}] {0.666074, {x -> -0.419282}} and even this form works... FindMinimum[fi[x], {x, 1}] {0.666074, {x -> -0.419282}} David Park djmp at earthlink.net http://home.earthlink.net/~djmp/