multiple linear regression, n-by-n vector of observed responses
7 views (last 30 days)
Show older comments
Hi everyone,
I’m new to MATLAB and I need some help.
I have a sample data set containing retunes of companies as well as two predictors variables collected along 5years. Now I need to run a multiple linear regression for the returns of each company. I am using b=regress(Y,X) but it works only with a vector Y (nx1). Having a matrix Y (nxn) (N companies x N time), how can I do it? Do I need a b=regress(Y,X) for every single vector Y or does it exist another way? Thank you very much for your help
0 Comments
Answers (2)
dpb
on 9 Apr 2014
Edited: dpb
on 9 Apr 2014
The loop over columns is one way, yes, but you can also do it in "one swell foop" using the "\" backslash operator mldivide for matrix left-divide.
For a set of underdetermined equations, it solves the least squares problem with good internal numerics. Set up your model as in regress excepting write it on an element-by-element basis (meaning use the dot operators) and then write
b=X\Y;
and you'll get a set of coefficients for each column in Y as each column of b.
For example, if your model were just a first order polynomial,
X=[x ones(size(x))];
b=X\Y
0 Comments
Shashank Prasanna
on 9 Apr 2014
Floriano, it appears that you are trying to perform multivariate linear regression. There are several ways to specify this problem. You can use dpb's approach for X\y where X(nxm) y(nxd) for any n,m and d. However if you want full covariance matrix for y (not diagonal) you can use mvregress:
5 Comments
Shashank Prasanna
on 10 Apr 2014
Floriano can confirm. Just to note, mvregress was added in R2006b:
See Also
Categories
Find more on Regression in Help Center and File Exchange
Community Treasure Hunt
Find the treasures in MATLAB Central and discover how the community can help you!
Start Hunting!