Bootstrap linear regression MSE

I am trying to use bootstrap on the MSE, R-squared output generated from linear regression model. However, I am having trouble figuring out how to set it up with the correct arguments.

I tried to do something like:

X1 = outcomes;
X2 = modcomes;
mdl = LinearModel.fit(X1, X2);

 resid = outcomes - modcomes;


% Simple bootstrap example
N_Boot = 1000;
SSE = zeros(N_Boot,1);
R_Sqrd = zeros(N_Boot,1);
for i = 1:N_Boot
     [foo_b , GoF_b] = LinearModel.fit(modcomes, outcomes + resid);
     SSE(i) = GoF_b.sse;
     R_Sqrd(i) = GoF_b.rsquare;
end
mean(SSE)
std(SSE)
mean(R_Sqrd)
std(R_Sqrd)

[Adam Danz]

If you're using matlab r2013b or later, you should use fitlm() instead of LinearModel.fit(). They have virtually the same inputs and both produce the LinearModel object. The model contains a field "Residuals" that contains (you guessed it) the residuals of the model. There is no documented second output and I haven't tried doing that myself so I'm not sure what's in the 2nd output in your code.

What are modcomes and outcomes?