ForecastEnsembles.jl

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Getting started ​

Welcome to the ForecastEnsembles documentation. This page is the quickstart. The home page is generated from the README and already carries the install instructions, so start here with what a new user does once the package is loaded, and grow it into tutorials as the package develops.

julia
using ForecastEnsembles

A first example ​

Wrap component forecasts in a ForecastTable and combine them with an EnsembleMethod:

julia
using ForecastEnsembles, DataFrames

df = DataFrame(
    location = "A", horizon = 1,
    model_id = repeat(["m1", "m2", "m3"], inner = 2),
    output_type = "quantile",
    output_type_id = repeat([0.25, 0.75], 3),
    value = [1.0, 3.0, 2.0, 4.0, 0.5, 2.5]
)

ft = ForecastTable(df; task_id_cols = [:location, :horizon])
combine(ft, QuantileEnsemble(:mean))
ForecastTable(
  models       = ["hub-ensemble"]
  output_type  = quantile
  task_id_cols = [:location, :horizon]
  rows         = 2
)

The Methods page explains the two axes — combination operation and weighting scheme — that organise the available ensembles.

Learning more ​

  • Want the full interface? See the Public API.

  • Want to report a problem or ask a question? Open an issue or start a discussion on the GitHub repository.

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