Regression using 1x6 table with 500x20 double elements

Hi all, i want to do a linear regression using fitlm. I created a table with 6 variables. The table consints of one row where each variable stores 500x20 double elements. I now want to do a linear regression with Var1 as Y and Var2-Var6 as X. So it should look like this:

Var1(row,i)=(alpha)+(beta1)*Var2(row,i)+(beta2)*Var3(row,i)+...

This has to be done for each row separate. So in the endeffect I should have 1 alpha and 5 Betas for 500 rows. That is my regression command i am trying to execute

    fitlm(Mytable,'Var1~Var2+Var3+Var4+Var5+Var6');

But i keep getting this error

Error using classreg.regr.FitObject/selectVariables (line 293)
Predictor variables must be numeric vectors, numeric matrices, or categorical vectors.

Can you please help me? Thanks

Answer 1

[Jeff Miller]

I'm not sure I fully understand your question, but maybe this will help: If you want one alpha and five betas for each of the 500 rows separately, then you will have to call fitlm 500 times. Each time you call it, you should pass only the data for one row.

[Hinti123]

ok. Yeah, that is exactly what I was expecting. Thanks for your help