&trans

Hi,

Do you know what is the function of &trans ? Thanks for taking time.

Best,

3 Answers



0



The ampersand in front of the word indicates that trans is a GAUSS procedure that is being passed into another GAUSS function which needs a user-defined procedure to call. I would look in the rest of the code that you are using to see if you can find the definition of the trans proc. It will start something like this

proc (1) = trans(a, b, c);

aptech

1,773


0



Related parts of the code is below. Thank you for taking time.

 

{x,fu,g,hh}=optprt(optmum(&ofn,startval));

x_out=trans(x);

 

gr=gradfd(&trans,x);

********

proc ofn(th1); @ ofn is the likelihood function

th is the vetor of params b|phi|d|se @

local like,A,R,th,Q,F,betat1_t1,Pt1_t1,j,betat_t1,Pt_t1,vt,Ft,fun,aa;

like=zeros(captst,1);

th=trans(th1);

 



0



There is a procedure named trans in the GAUSS time series application module TSMT. It takes one input vector as an argument and returns one output vector of the same size, so it could work as a function passed to a gradient computing function, like gradfd. I think you need this function from the TSMT package.

aptech

1,773

Your Answer

3 Answers

0

The ampersand in front of the word indicates that trans is a GAUSS procedure that is being passed into another GAUSS function which needs a user-defined procedure to call. I would look in the rest of the code that you are using to see if you can find the definition of the trans proc. It will start something like this

proc (1) = trans(a, b, c);

0

Related parts of the code is below. Thank you for taking time.

 

{x,fu,g,hh}=optprt(optmum(&ofn,startval));

x_out=trans(x);

 

gr=gradfd(&trans,x);

********

proc ofn(th1); @ ofn is the likelihood function

th is the vetor of params b|phi|d|se @

local like,A,R,th,Q,F,betat1_t1,Pt1_t1,j,betat_t1,Pt_t1,vt,Ft,fun,aa;

like=zeros(captst,1);

th=trans(th1);

 

0

There is a procedure named trans in the GAUSS time series application module TSMT. It takes one input vector as an argument and returns one output vector of the same size, so it could work as a function passed to a gradient computing function, like gradfd. I think you need this function from the TSMT package.


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