NMininimize vs. FIndMinimum with NDSolve?

*To*: mathgroup at smc.vnet.net*Subject*: [mg51135] NMininimize vs. FIndMinimum with NDSolve?*From*: Manuel Morales <Manuel.A.Morales at williams.edu>*Date*: Tue, 5 Oct 2004 04:37:45 -0400 (EDT)*Sender*: owner-wri-mathgroup at wolfram.com

Is it possible to use NMinimize to estimate parameters for a differential equation solved with NDSolve? I *am* able to use FindMinimum, but NMinimize doesn't seem to work... Here is what I am doing using FindMinimum: sse[r_?NumberQ, q_?NumberQ] := Block[{sol, f}, Plus @@ Table[ sol = NDSolve[{f'[t] == r f[t] + q f[t]^2, f[0] == data[[i]][[1]][[2]]}, f, {t, 0, 10}][[1]]; Plus @@ Apply[(f[#1] - #2)^2 &, data[[i]], {1}] /. sol, {i, 1, Length[data]}]]; params = FindMinimum[sse[r, q], {r, .1, .2}, {q, -.001, -.002}] However, using NMinimize to estimate doesn't work. That is, if I replace the last line with: params = NMinimize[sse[r, q], {r, q}] I get a bunch of error messages. Thanks for any help. If anyone wants to try this, you can generate a test data set below: Block[{r, q}, r = .5; q = -.001; data = Table[ sol = NDSolve[{f'[t] == r f[t] + q f[t]^2, f[0] == j}, f, {t, 0, 10}][[1]]; Table[{i, f[i] /. sol}, {i, 0, 10, 2}], {j, 1, 301, 150}] ] Manuel