Constraints on Parameter Estimation

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Faizan Lali
Faizan Lali 2023-3-11
评论： Torsten 2023-3-13
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 2023-3-11
Use lsqlin instead of fitlm.
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Torsten
Torsten 2023-3-13
This is the best fit you can get without intercept and the constraints you want to impose on the parameters.
Torsten
Torsten 2023-3-13
@Matt J
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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