I think the question was for prediction intervals. I don't see that in GLM, yet.
On Wed, Apr 1, 2015 at 12:48 PM, <[email protected]> wrote: > GLM.jl have prediction methods for Linear and Generalized Linear Models. > They take corresponding models and features as input. Please see for > implementation details > [glm] > https://github.com/JuliaStats/GLM.jl/blob/a7fb0057a7bc835d819e842c6f42f14601840a1b/src/glmfit.jl#L249 > and > [lm] > https://github.com/JuliaStats/GLM.jl/blob/4f862cf11a93d2c91ce5e745f51233c49941f836/src/lm.jl#L77 > > If your inputs are in dataframe format, DataFrames.jl gives nice wrappers > so that you can input DataFrameRegressionModel and DataFrames instead. > Please see for details > > https://github.com/JuliaStats/DataFrames.jl/blob/b6e65259c9b0d74187f06cb6e4e9302b9f1c9106/src/statsmodels/statsmodel.jl#L69 > > These implementations are overloads of functions in StatsBase > https://github.com/JuliaStats/StatsBase.jl/blob/e6411b644c02d470036d44fe25a49cdf89a15fff/src/statmodels.jl#L21 > > I have used these methods with success. Please let me know if these don't > work for your case. > > Best wishes! > > > On Wednesday, April 1, 2015 at 1:50:08 AM UTC-4, Christopher Fusting wrote: >> >> Thanks. I've found confidence intervals, still looking for prediction. >> >> Cheers, >> >> _Chris >> >> On Tuesday, March 31, 2015 at 4:53:37 PM UTC-4, Patrick Kofod Mogensen >> wrote: >>> >>> I do believe GLM.jl has this. >> >>
