Azzera filtri
Azzera filtri

Constraints on Parameter Estimation

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Faizan Lali
Faizan Lali il 11 Mar 2023
Commentato: Torsten il 13 Mar 2023
I am trying to fit linear regression model and predict parameters without intercept. I have written my code as under;
tbl=table(yobs,x1,x2,x3);
mdl = fitlm(tbl,'yobs ~ x1 + x2 + x3 - 1')
but I am getting the estimates which are negative but in my model all parameters should be positive. LB>=0 and UB=inf. How to set these constraints while doing the prediction.

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Torsten
Torsten il 11 Mar 2023
Use lsqlin instead of fitlm.
  6 Commenti
Torsten
Torsten il 13 Mar 2023
This is the best fit you can get without intercept and the constraints you want to impose on the parameters.
Torsten
Torsten il 13 Mar 2023
According to the documentation,
yobs ~ x1 + x2 + x3 - 1
means a three-variable linear model without intercept.
Thus the "-1" just means: no constant term, not
yobs = p1*x1 + p2*x2 + p3*x3 - 1
Very confusing.

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