I copied the following answer to FAC due to Feiveson. I hope that this help
you. Henrique
How can I use Stata to solve a system of nonlinear equations?
Title Using Stata to solve a system of nonlinear equations
Author Alan H. Feiveson, NASA
Date June 2001; updated October 2005
----------------------------------------------------------------------------
----
Suppose that you want to solve
f1(a1,...,an) = 0
f2(a1,...,an) = 0
.
.
.
fn(a1,...,an) = 0
(n nonlinear equations in n unknowns a1,..,an)
First, rewrite the first equation such that its right-hand side is 1:
f1(a1,...,an) + 1 = 1
f2(a1,...,an) = 0
.
.
.
fn(a1,...,an) = 0
Then, set up a fake dataset with n observations as follows:
The dependent variable y takes on the value 1 for the first observation and
0 for all the others. Stata's nl estimation won't work if y is a constant,
so you need to write the first equation so that the "right-hand sides" are
not all the same; that is why I reformulated the problem above. In this
example, I used one for the first observation and zero for the others.
Write an nl program that fills in the dependent variable passed to it with
the values of the functions. Suppose n=3. Then your program should look
something like this:
program nlfaq
syntax varlist (min=1 max=1) [if], at(name)
tempname a1 a2 a3
scalar `a1' = `at'[1, 1]
scalar `a2' = `at'[1, 2]
scalar `a3' = `at'[1, 3]
tempvar yh
generate double `yh' = f1(`a1', `a2', `a3') in 1
replace `yh' = f2(`a1', `a2', `a3') in 2
replace `yh' = f3(`a1', `a2', `a3') in 3
replace `varlist' = `yh'
end
nl requires that our program accept an if clause, though we can ignore it in
our program since we do not have missing data and will not be restricting
the estimation sample when calling nl.
Call nl with y as the dependent variable, specifying initial values for a1,
a2, ..., an at which the functions can be evaluated.
Here is an example. Suppose that I want to solve the following system for A,
B, and C:
exp(A) + B*C = 3
A/B + C^2 = log(B)
A/(A+B+C) = sin(C)
Here is my nl program:
program nlfaq
syntax varlist(min=1 max=1) [if], at(name)
tempname A B C
scalar `A' = `at'[1, 1]
scalar `B' = `at'[1, 2]
scalar `C' = `at'[1, 3]
tempvar yh
gen double `yh' = exp(`A') + `B'*`C' - 2 in 1
replace `yh' = `A'/`B' + `C'^2 - log(`B') in 2
replace `yh' = `A'/(`A'+`B'+`C') - sin(`C') in 3
replace `varlist' = `yh'
end
Now I generate the dataset that nl requires:
. clear
. set obs 3
obs was 0, now 3
. generate y = 0
. replace y = 1 in 1
(1 real change made)
I estimate using nl:
. nl faq @ y, parameters(A B C) initial(A 1 B 1 C 1)
(obs = 3)
Iteration 0: residual SS = .5792985
Iteration 1: residual SS = .0364809
Iteration 2: residual SS = .0001378
Iteration 3: residual SS = 2.92e-09
Iteration 4: residual SS = 1.43e-18
Iteration 5: residual SS = 2.25e-31
Source | SS df MS
-------------+------------------------------ Number of obs =
3
Model | 1 3 .333333333 R-squared =
1.0000
Residual | 1.6332e-31 0 . Adj R-squared =
.
-------------+------------------------------ Root MSE =
.
Total | 1 3 .333333333 Res. dev. =
-207.451
----------------------------------------------------------------------------
--
y | Coef. Std. Err. t P>|t| [95% Conf.
Interval]
-------------+--------------------------------------------------------------
--
/A | .8973072 . . . .
.
-------------+--------------------------------------------------------------
--
/B | 1.803287 . . . .
.
-------------+--------------------------------------------------------------
--
/C | .3033412 . . . .
.
----------------------------------------------------------------------------
--
* (SEs, P values, CIs, and correlations are asymptotic approximations)
Finally, I verify the solution:
. scalar A = [A]_b[_cons]
. scalar B = [B]_b[_cons]
. scalar C = [C]_b[_cons]
. di exp(A) + B*C
3
. di A/B + C^2 " " log(B)
.58961117 .58961117
. di A/(A+B+C) " " sin(C)
.29871053 .29871053
-----Mensagem original-----
De: [email protected]
[mailto:[email protected]] Em nome de Craig Martin
Enviada em: quarta-feira, 19 de dezembro de 2007 17:14
Para: [email protected]
Assunto: st: Estimation of a non-linear system of equations
I am using Stata 9 and need to estimate a system of equations.
I can estimate each equations separately using nl. However, when I try
to estimate the system using the same syntax as linear estimation for a
system of equations, I get a varlist error. What is the syntax or how
do you estimate a non-linear system of eqation in Stata 9.0?
Thanks,
--
Craig Martin M.Sc.
PhD Candidate
Department of Food, Agricultural and Resource Economics
University of Guelph
Guelph, Ontario N1G 2W1
(519) 824-4120 Ext. 58315
Fax (519) 767-1510
*
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