"mvregress" does not do Multivariate Linear Regression?

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The documentation for function "mvregress" states that the return value "beta" is a vector of the regression coefficients. Looking deeper into "Multivariate Normal Regression", we see that matlab uses the same regression coefficients ("beta") for every dimension of the multivariate response variable Y
This is ludicrous. Of course each component of the response variable can have its own set of coefficients. THAT is multivariate linear regression.
Am I missing something? Is this just an inherent shortcoming in matlab's "mvregress" function? If so, what a bizarre design choice...
Is there some way to get real multivariate linear regression, i.e. get a matrix beta of regression coefficients?
Ricardo Arévalo
Ricardo Arévalo on 18 Oct 2016
If you use regress, remember to add a column of ones to indicate that there is a constant in your regression model.
I leave an example:
%Let lon, lat and alt be the independant variables of a model.
%Let pre be the dependant variable of the model.
%Adding a column of ones to get the constant.
%This will create a regression model of type:
% Pre=a0+(a1*lon)+(a2*lat)+(a3*alt), it also gives stats and residuals
[b,bint,r,rint,stats] = regress(pre,predictors);

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Accepted Answer

the cyclist
the cyclist on 16 Mar 2013
Edited: the cyclist on 16 Mar 2013
You are missing something. See my answer in this thread for several examples of using design matrices with mvregress():
There are also examples from MathWorks here: http://www.mathworks.com/help/stats/mvregress.html
the cyclist
the cyclist on 23 Jan 2016
Although this is a perfectly sensible place to ask this question, you won't actually get much attention from a comment buried in a 3-year-old thread.
I suggest you ask a new question. If you can actually attach files with your data and code, that will help people diagnose your issue.

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