Linear regression with categorical predictor & quadratic term - dataset

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Tania 2014-6-12

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https://ww2.mathworks.cn/matlabcentral/answers/133931-linear-regression-with-categorical-predictor-quadratic-term-dataset

评论： Tania 2014-6-14

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Hey!

I am trying to construct a dataset array as below(matlab help) in order to do a regression:

>> load carsmall
>> ds = dataset(MPG, Weight);
>> ds.Year=nominal(Model_Year);
>> mdl = fitlm(ds, 'MPG~Year+Weight^2')
mdl = 
Linear regression model:
    MPG ~ 1 + Weight + Year + Weight^2
Estimated Coefficients:
                   Estimate      SE            tStat      pValue    
    (Intercept)        54.206        4.7117     11.505    2.6648e-19
    Weight          -0.016404     0.0031249    -5.2493    1.0283e-06
    Year_76            2.0887       0.71491     2.9215     0.0044137
    Year_82            8.1864       0.81531     10.041    2.6364e-16
    Weight^2       1.5573e-06    4.9454e-07      3.149     0.0022303
Number of observations: 94, Error degrees of freedom: 89
Root Mean Squared Error: 2.78
R-squared: 0.885,  Adjusted R-Squared 0.88
F-statistic vs. constant model: 172, p-value = 5.52e-41

But unfortunately, i get an error message when I try to do it with my data:

>> ds=dataset(price, size, weight, speed);
>> ds.postcode=nominal(postcode);
 mdl = fitlm(ds, 'price~postcode+size+weight+speed')

Which is:

Index of element to remove exceeds matrix dimensions.
Error in classreg.regr.modelutils.designmatrix>dummyVars (line 432)
    X0 = eye(ng); X0(:,1) = [];
Error in classreg.regr.modelutils.designmatrix (line 279)
            [Xj,dummynames] = dummyVars(dummyCoding{j},Xj,catLevels{j});
Error in classreg.regr.TermsRegression/designMatrix (line 316)
                [design,~,~,coefTerm,coefNames] ...
Error in LinearModel/fitter (line 654)
            [model.Design,model.CoefTerm,model.CoefficientNames] =
            designMatrix(model,X);
Error in classreg.regr.FitObject/doFit (line 220)
            model = fitter(model);
Error in LinearModel.fit (line 857)
            model = doFit(model);
Error in fitlm (line 111)
model = LinearModel.fit(X,varargin{:});

Thank you for your help!

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dpb 2014-6-13

编辑：dpb 2014-6-13

在 MATLAB Online 中打开

I don't know; Rsq is only roughly 40% (leaving 60% of total unexplained) and just glancing thru it appears that a very few of the coefficients are significant out of the "cast of thousands". Superficially I wouldn't say it looks like a very good model and certainly isn't high on the candidates list for a parsimonious one... :)

I'd guess the model estimated on only

 (Intercept)        0.090898
    bedroom          1.0747e-22
    postcode_NW1       0.072403
    postcode_SW1X      0.026157

would perform nearly as well.

Tania 2014-6-14

Thanks, this is just the beginning for me.will try to work with the data with other models afterwards and hopefully get better results. but this help me a lot to get my first matlab analysis working. thanks :)

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