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Nov 27 at 22:07 comment added mark leeds Darek: I was just pointing out that it looks similar to multivariate regression. minginator seems to have a good grip on this material ( I don't ) so it's best to let him help you. And thanks to minginator for expressing my comment more clearly.
Nov 26 at 16:47 comment added minginator Darek, you are referring to now is multiple regression, @markleeds is referring to an equation of the form $Y = XB + \varepsilon$ where $Y$ and $\varepsilon$ are $n \times p$ matrices, $X$ is $n \times q$ matrix and $B$ is $q \times p$ (I use $n$ to denote sample size, if you take $n = 1$ and the transpose you would get the model in your post for a single observation). You may find more if you search for Seemingly Unrelated Regressions (SUR), or e.g. here (bashtage.github.io/linearmodels/system/…).
Nov 26 at 16:03 history edited Darek CC BY-SA 4.0
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Nov 26 at 16:01 comment added Darek @markleeds In multivariate regression on left hand side we have $Y$ which is a $n \times 1$ vector. In this model $Y$ is form as $n$ vectors each one $k$ dimensional. Thanks - you are right about $\epsilon$
Nov 26 at 15:58 history edited Darek CC BY-SA 4.0
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Nov 26 at 15:36 comment added mark leeds I haven't seen that before myself but it's pretty similar to multivariate regression. See this for the similarities. brilliant.org/wiki/multivariate-regression Note that you can't have a scalar $\epsilon$ if you have a vector response.
Nov 26 at 14:12 review Close votes
Nov 27 at 10:38
Nov 26 at 13:56 history asked Darek CC BY-SA 4.0