Linear regression model with fitlm

I have two arrays and I am doing a weighted correlation with the function fitlm.

If I write:

tbl = table(ones(9,1),a(:),b(:),'VariableNames',{'Weight','array1','array2'});

correlation = fitlm(tbl)

I get:

correlation =

Linear regression model: map2 ~ 1 + Weight + map1

Estimated Coefficients: Estimate SE tStat pValue ______ _____ ______ ______

    (Intercept)     0.66696    0.24971       2.671    0.036979
    Weight                0          0         NaN         NaN
    map1           -0.22041    0.39988    -0.55119     0.60141

Number of observations: 9, Error degrees of freedom: 7 Root Mean Squared Error: 0.292 R-squared: 0.0416, Adjusted R-Squared -0.0953 F-statistic vs. constant model: 0.304, p-value = 0.599

In correlation I can find almost all the values printed in the workspace, with the exeption of the p-value = 0.599

Why? Where is it and what is it?

Thank you.

Answer 1

[Star Strider]

You may have to do a separate anova call to get it:

Anova = anova(correlation);
AnovaP = Anova.pValue(2);

That works for your model.

(I usually am interested in the coefficient statistics, that are generally easier to recover.)

[Marianna]

That works, thank you.

Yes, my problem was to check the significance of the correlation.

[Star Strider]

My pleasure.

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