lm interface with X as a vector instead of a matrix to enable a simple interface for simple linear regression

[ajinkya-k]

Hello!

I have been playing around with GLM.jl and I had a question/request.

I am not very comfortable with Julia yet and tried to run lm(vector_X, vector_Y) thinking it might work but got an error fit(::Type{LinearModel}, ::Vector{Float64}, ::Vector{Float64}, ::Nothing)

So my question is: Do you think it would be worth adding a vector on vector lm method, i.e. fit(::Type{LinearModel}, ::Vector{Float64}, ::Vector{Float64}, ::Nothing) for simple linear regression when there is a single covariate? Such a method would need to automatically add an intercept column and run the regression? I know that one could always use the formula interface but I was just curious if you think such a method should be added. Feel free to ignore this request if you feel this will not have more general utility.