Thanks Taylor, added predict method to documentation.
Bradley
On Sunday, August 31, 2014 9:34:51 PM UTC-5, Taylor Maxwell wrote:
>
> Are you looking for the fitted values? Is predict(OLS) what you are
> looking for?
>
> *julia> **X = [1;2;3.]*
>
> *3-element Array{Float64,1}:*
>
> * 1.0*
>
> * 2.0*
>
> * 3.0*
>
>
> *julia> **Y = [1;0;1.]*
>
> *3-element Array{Float64,1}:*
>
> * 1.0*
>
> * 0.0*
>
> * 1.0*
>
>
> *julia> **data = DataFrame(X=X,Y=Y)*
>
> *3x2 DataFrame*
>
> *|-------|-----|-----|*
>
> *| Row # | X | Y |*
>
> *| 1 | 1.0 | 1.0 |*
>
> *| 2 | 2.0 | 0.0 |*
>
> *| 3 | 3.0 | 1.0 |*
>
>
> *julia> **OLS = glm(Y~X,data,Normal(),IdentityLink())*
>
> *DataFrameRegressionModel{GeneralizedLinearModel,Float64}:*
>
>
> *Coefficients:*
>
> * Estimate Std.Error z value Pr(>|z|)*
>
> *(Intercept) 0.666667 1.24722 0.534522 0.5930*
>
> *X -4.16334e-16 0.57735 -7.21111e-16 1.0000*
>
>
>
> *julia> **predict(OLS)*
>
> *3-element Array{Float64,1}:*
>
> * 0.666667*
>
> * 0.666667*
>
> * 0.666667*
>
>
>
>
