Call a procedure after optimisation

Question

I have a procedure for an optimization problem (with OPTMT 2.0), but I would like to call that procedure later only to obtain the function value with a different parameter vector.

Here is the procedure:

proc (1) = ch5_lmpost(pars, y, X, ind);
    local fgamma, lmarg_post;

    struct modelResults mm;

    fgamma = pars[2:3]' * (x[., 2:3].^pars[4])';
    fgamma = fgamma.^(1 / pars[4]);
    fgamma = fgamma' + pars[1] .* ones(n, 1);

    // Evaluate the log marginal posterior
    lmarg_post = 0.5 * n * ln((y - fgamma)'(y - fgamma));

    if ind[1];
        mm.Function = lmarg_post;
    endif;

retp(mm);
endp;

The optimization works perfectly, but how do I call the procedure afterwards if I just want to get the function value?

2 Answers

Your Answer

aptech · Answer 1

Here is an example of calling your function with some simulated data.

new;
cls;

library optmt; 

// Replace with your parameters
b = {  0.4, 1.1, 0.8, 0.9 };

// Load your data instead
y = rndu(100, 1);
X = rndu(100, 4);

// Declare a modelResults structure to hold the return value
struct modelResults rslt;

// Call the function with your  desired inputs
rslt = ch5_lmpost(b, y, X, 1);
print rslt.function;

proc (1) = ch5_lmpost(pars, y, X, ind);
    local fgamma, lmarg_post, n;

    struct modelResults mm;

    // 'n' was not set in the original post.
    // I'm not sure it is set correctly here,
    // you may need to change it.
    n = rows(X);

    fgamma = pars[2:3]' * (x[., 2:3].^pars[4])';
    fgamma = fgamma.^(1 / pars[4]);
    fgamma = fgamma' + pars[1] .* ones(n, 1);

    // Evaluate the log marginal posterior
    lmarg_post = 0.5 * n * ln((y - fgamma)'(y - fgamma));

    if ind[1];
        mm.Function = lmarg_post;
    endif;

retp(mm);
endp;

Let us know if you have any questions about this.

link

aptech

1,773

sebszab · Answer 2

Ok, so I need to define a structure for the function value. I tried it too, but somehow it didn't work. Now it does. Thanks very much!

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sebszab

22

aptech · Answer 3

Here is an example of calling your function with some simulated data.

new;
cls;

library optmt; 

// Replace with your parameters
b = {  0.4, 1.1, 0.8, 0.9 };

// Load your data instead
y = rndu(100, 1);
X = rndu(100, 4);

// Declare a modelResults structure to hold the return value
struct modelResults rslt;

// Call the function with your  desired inputs
rslt = ch5_lmpost(b, y, X, 1);
print rslt.function;

proc (1) = ch5_lmpost(pars, y, X, ind);
    local fgamma, lmarg_post, n;

    struct modelResults mm;

    // 'n' was not set in the original post.
    // I'm not sure it is set correctly here,
    // you may need to change it.
    n = rows(X);

    fgamma = pars[2:3]' * (x[., 2:3].^pars[4])';
    fgamma = fgamma.^(1 / pars[4]);
    fgamma = fgamma' + pars[1] .* ones(n, 1);

    // Evaluate the log marginal posterior
    lmarg_post = 0.5 * n * ln((y - fgamma)'(y - fgamma));

    if ind[1];
        mm.Function = lmarg_post;
    endif;

retp(mm);
endp;

Let us know if you have any questions about this.

link

aptech

1,773