Osr optim_weights, need clarification

Dear all,

In the OSR code we have the optim_weights set like this :

inf 1;
y 1;

As I understand, this means the same weight “0.5” for each variable.
But if I have my quadratic loss function as this one :
(1-lambda)inflation^2 + lambdax^2

According to optim_weights, how can I set the weight 0.70 (=1-lambda) for inflation and 0.30 (=lambda) for x?
Indeed, which discount value (beta) is used in the quadratic OSR code, as I can set the dicount value as in ramsey code.
thanks for yor help !


regarding what you wrote previous, this means you assign a weight of 1 to each variables that is, inflation and output.
Now if you wanna assign different values (using parameter lambda), you just need to replace the weights “1” with lambda and 1-lamdda as follows
inf lambda;
y 1-lambda;