non linear regression code
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I did linear regression by the code below. data set is attached.
clear;
clc
load('data.mat');
F=F'; T=T'; W=W';
Q1=F;
Q2=T;
X=[Q1 Q2];
for i=1:70
Y=W(:,i);
% b = regress(Y,X,0.05);
mdl{i} = fitlm(X,Y);
XX{i}= mdl{i}.Coefficients;
rmqs(i)=mdl{i}.RMSE;
for j=1:3
b(i,j)=XX{i}{j,1};
er(i,j)=XX{i}{j,2};
end
end
I want to change this code to fit the data for a non-linear model. which is,
Y~b0+b1*Q1+b2*Q2+b3*cos(2*pi*T+b4)
instead,
Y~b0+b1*Q1+b2*Q2
I need the coefficients with errors. How can I do that?
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Answers (1)
Brendan Hamm
on 12 Aug 2015
Is T a predictor variable in this equation or a constant? If it is a constant you would want to create a function handle (which nlinfit requires anyhow, but fitnlm accepts). If it is a predictor you would need to place it in the matrix X and you can pass the modelspec in fitnlm as:
modelspec = 'y~b1+b2*x1+b3*x2+b4*cos(2*pi*x3+b5)';
I imagine you would want to estimate the frequency as well, unless this is known a priori.
4 Comments
Brendan Hamm
on 13 Aug 2015
As useful as google sounds like a complement, thank you. I might have to place that on my resume.
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