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Constained regression 2 - regression model/solver

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Simon Wang
Simon Wang 2015-3-15
关闭： MATLAB Answer Bot 2021-8-20
I have a regression model log (r(i)) = a + b * log(A(i)) where A(i) is a vector and each element is known. Log is the nature log.
I need to find out a, b, and each element of r(i) such that the sum of r(i) equals to a constant k and the sum of error, sum(square[log (r(i)) – log(P(i)])is minimized, here each element in vector P(i) is known. a and b are scalars.
What regression model/solver should I choose? How to accomplish this gooal?
Thanks!
  2 个评论
John D'Errico
John D'Errico 2015-3-15
编辑：John D'Errico 2015-3-15
A virtually identical re-ask of your last question, except that in this version, the main difference is you added the Thanks! at the end.
http://www.mathworks.com/matlabcentral/answers/182905-what-constrained-regression-function-shuld-i-use

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回答（1 个）

Torsten
Torsten 2015-3-16
min: sum_{i=1}^{N} (log((a+b*log(A(i))/P(i)))^2
under the constraint
exp(a)*sum_{i=1}^{N} A(i)^b - k = 0
Use fmincon to solve for a and b.
Best wishes
Torsten.

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