Le jeudi 29 septembre 2016 à 09:47 -0700, Min-Woong Sohn a écrit :

> As a followup, I realized that GLM put the interaction variable at

> the end of the estimates in the coeftable output. Is there any way I

> can preserve the order such that the variables are shown in order

> (e.g., LStat, Age, and LStat and Age intertion in that order).

What's the problem exactly with the output shown in the message below?

Don't you get the same result?

Regards

> > I think the problem is with third and higher order interactions.

> >

> > > It works fine for me although I am using the latest master

> > > version of GLM so I need to use fit(LmMod, formula,df)

> > >

> > > using RDatasets, GLM

> > > boston = dataset("MASS", "Boston")

> > >

> > > julia> cc=fit(LmMod,MedV ~ LStat+Age+LStat&Age, boston)

> > > DataFrameRegressionModel{LmMod{DensePredQR{Float64}},Float64}:

> > >

> > > Coefficients:

> > > Estimate Std.Error t value Pr(>|t|)

> > > (Intercept) 36.0885 1.46984 24.5528 < eps()

> > > LStat -1.39212 0.167456 -8.31335 8.8e-16

> > > Age -0.00072086 0.0198792 -0.0362621 0.9711

> > > LStat & LStat 0.00415595 0.0018518 2.24428 0.0252

> > >

> > >

> > > > How do you specify interactions and non-linear transforms using

> > > > the fomula for GLM? Something like y~x1*x2 + x2^2

> > > >

> > >

> >

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