I haven't seen code to do it yet but it is very simple to calculate with a
LinearModel from GLM Below is some code to calculate r-squared or adjusted
r-squared from a linear model in GLM calculated from a dataframe or from a
model calculated without a data frame. At the bottom is some simple code
to apply these functions. It uses the Abs2Fun() from the NumericFuns
package to calculate the sum of squares quickly.
using DataFrames
using GLM
import DataFrames.DataFrameRegressionModel
import GLM.LinearModel
import GLM.residuals
using NumericFuns
function
rsquared(mod::DataFrameRegressionModel{LinearModel{DensePredQR{Float64}},Float64})
SStot=sum(Abs2Fun(),mod.model.rr.y)
SSres=sum(Abs2Fun(),residuals(mod))
return (1-(SSres/SStot))
end
function rsquared(mod::LinearModel{DensePredQR{Float64}})
SStot=sum(Abs2Fun(),mod.rr.y)
SSres=sum(Abs2Fun(),residuals(mod))
return (1-(SSres/SStot))
end
function
adjrsquared(mod::DataFrameRegressionModel{LinearModel{DensePredQR{Float64}},Float64})
SStot=sum(Abs2Fun(),mod.model.rr.y)
SSres=sum(Abs2Fun(),residuals(mod))
n=size(mod.model.rr.y,1) #number of samples
p=size(mod.mm.m,2)-1 #number of variables besides constant (assumes
intercept)
return 1- ( (SSres/(n-p-1)) / (SStot/(n-1)) )
end
function adjrsquared(mod::LinearModel{DensePredQR{Float64}})
SStot=sum(Abs2Fun(),mod.rr.y)
SSres=sum(Abs2Fun(),residuals(mod))
n=size(mod.rr.y,1) #number of samples
p=size(mod.pp.X,2)-1 #number of variables besides constant (assumes
intercept)
return 1- ( (SSres/(n-p-1)) / (SStot/(n-1)) )
end
dd=randn(1000,7);
df=convert(DataFrame,dd);
aa=fit(LinearModel,x1~x2+x3+x4+x5+x6,df)
bb=fit(LinearModel,aa.mm.m,aa.model.rr.y)
rsquared(aa)
adjrsquared(aa)
rsquared(bb)
adjrsquared(bb)
On Wednesday, August 6, 2014 5:33:15 PM UTC-6, Jason Solack wrote:
>
> Hello everyone. I am looking for a way to run this regression and
> retrieve the corresponding r squared value. Is there a package out there
> that does this?
>
> Thank you for the help!
>
> Jason
>
