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. > >
