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st: RE: nonlinear programming


From   "FEIVESON, ALAN H. (AL) (JSC-SK) (NASA)" <alan.h.feiveson@nasa.gov>
To   "'statalist@hsphsun2.harvard.edu'" <statalist@hsphsun2.harvard.edu>
Subject   st: RE: nonlinear programming
Date   Thu, 3 Feb 2005 12:54:42 -0600

Are you trying to solve a nonlinear system of equations? If so, there is a
FAQ on this - try typing:

findit solve nonlinear system

AL FEiveson

-----Original Message-----
From: owner-statalist@hsphsun2.harvard.edu
[mailto:owner-statalist@hsphsun2.harvard.edu]On Behalf Of Joy Chen
Sent: Wednesday, February 02, 2005 2:34 PM
To: Stata List
Subject: st: nonlinear programming


Hi,

I am working on a nonlinear programming and I got problems with the
progamming and the results. I wonder whether anyone that knows nonlinear
programming could help me a little bit.
Here is my programming:

capture program drop nlprog

program define nlprog
	 version 8.0
            if "`1'" == "?" {
                	global S_1 "B0 B1 B5"
                	global B0=1
                	global B1=1
		 global B5=-1
		 exit
            }
            replace	`1'=(1/$B0) *$B5* (exp((e - $B0*f)* $B1)-exp(- (e-
$B0*f) * $B1))
      	end

nl prog f, eps(1e-3)

There are two variables in the dataset, e and f. In the -replace- line, I
have the variable f in RHS. f is my dependent variable as well in nl
regression. ( I am not sure whether this setup will cause a problem.) But i
couldn't solve f explicitly for a system of nonlinear equations.
 It never converges even after more than 1000 iterations. When i set
esp(1e-3) instead of the default one, 1e-5, i got the following results,
which are quite far away from those existing in the literature (B0 must be
0.075, B1 must be around 9 and B5 around -1.5).

........
Iteration 88:  residual SS =  1.31e-06
Iteration 89:  residual SS =  1.31e-06

      Source |       SS       df       MS            Number of obs =
138
-------------+------------------------------         F(  2,   135) =
2.20e+09
       Model |  42.5278108     2  21.2639054         Prob > F      =
0.0000
    Residual |  1.3044e-06   135  9.6625e-09         R-squared     =
1.0000
-------------+------------------------------         Adj R-squared =
1.0000
       Total |  42.5278121   137  .310421986         Root MSE      =
.0000983
                                                     Res. dev.
    = -2158.198
(prog)
----------------------------------------------------------------------------
--
           f |      Coef.   Std. Err.      t    P>|t|     [95% Conf.
Interval]
-------------+--------------------------------------------------------------
--
          B0 |   2245.996   .0252551        .   0.000     2245.946
2246.046
          B1 |   .0000104   1.46e-10        .   0.000     .0000104
.0000104
          B5 |  -47949.21   .6685612        .
0.000    -47950.53   -47947.89
----------------------------------------------------------------------------
--
* Parameter B0 taken as constant term in model & ANOVA table
 (SEs, P values, CIs, and correlations are asymptotic approximations)

I am stuck at this point quite a few days. It would be really nice if anyone
could give me some suggestion or diagonosis.

Best.


Joy Chen
Munich Graduate School of Economics
University of Munich
Kaulbachstraße 45
D-80539 Munich / Germany
Email: Joy.Chen@lrz.uni-muenchen.de


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