LinearModel.fit results to array

Hi,

I would like to ask about results from LinearModel.fit function. I used the function and it ran smoothly. However, I could not extract the result properly.

I have a 100 set of X and Y. What I would like to have is a array showing coefficient and R-square of all. I basically try to do a loop and have LinearModel.fit function inside. My problem is I could not write out coefficient from mdl.Coefficients and r-square from mdl.Rsquared.Ordinary value to save into my array.

I crated array 100 x 1 to save R-square value from each set. To sum up, how can I save the values of results from each set to array?

Thank you.

Answer 1

[Leah]

I was able to do it, i made a dataset mid to hold everything

md = LinearModel.fit()
mid.RsqAdj=md.Rsquared.Adjusted;
mid.Intercept=md.Coefficients.Estimate(1);

          for c=2:length(md.CoefficientNames)
              mid.(md.CoefficientNames{c})=md.Coefficients.Estimate(c);
          end

[OoM]

Thank you very much.

[OoM]

mid.RsqAdj=md.Rsquared.Adjusted

gave me

mid =

    Rsq: 0.8690

It is in struct format. Any way to transform it to array

Rsq = [0.8690]

Answer 2

[the cyclist]

mdl.Coefficients

is a variable of type dataset.

mdl.Coefficients.Estimate

will be an array of doubles, which I think is what you need.

[OoM]

I tried to call only mdl.Coefficients.Estimate. It does not work.

[the cyclist]

Does calling this code give you a 5x1 double for mdl.Coefficients.Estimate?

load hald
X = ingredients; % predictor variables
y = heat; % response
mdl = LinearModel.fit(X,y)
mdl.Coefficients.Estimate

Answer 3

[OoM]

I am able to get R-squared from

rsq = mdl.Rsquared.Ordinary

rsq =

    0.8690

and only coefficient from

Coefficient = mdl.Coefficients.Estimate(:,1)

Coefficient =

   1.0e+05 *

    1.4231
   -0.0012