_            _    _        _         _
      /\ \         /\ \ /\ \     /\_\      / /\
      \_\ \       /  \ \\ \ \   / / /     / /  \
      /\__ \     / /\ \ \\ \ \_/ / /     / / /\ \__
     / /_ \ \   / / /\ \ \\ \___/ /     / / /\ \___\
    / / /\ \ \ / / /  \ \_\\ \ \_/      \ \ \ \/___/
   / / /  \/_// / /   / / / \ \ \        \ \ \
  / / /      / / /   / / /   \ \ \   _    \ \ \
 / / /      / / /___/ / /     \ \ \ /_/\__/ / /
/_/ /      / / /____\/ /       \ \_\\ \/___/ /
\_\/       \/_________/         \/_/ \_____\/
r-modeltime-ensemble 1.0.4
Propagated dependencies: r-yardstick@1.3.2 r-workflows@1.2.0 r-tune@1.3.0 r-timetk@2.9.0 r-tidyr@1.3.1 r-tictoc@1.2.1 r-tibble@3.2.1 r-stringr@1.5.1 r-rsample@1.3.0 r-rlang@1.1.6 r-recipes@1.3.1 r-purrr@1.0.4 r-modeltime-resample@0.2.3 r-modeltime@1.3.1 r-magrittr@2.0.3 r-glmnet@4.1-8 r-generics@0.1.4 r-foreach@1.5.2 r-dplyr@1.1.4 r-doparallel@1.0.17 r-cli@3.6.5
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://business-science.github.io/modeltime.ensemble/
Licenses: Expat
Synopsis: Ensemble Algorithms for Time Series Forecasting with Modeltime
Description:

This package provides a modeltime extension that implements time series ensemble forecasting methods including model averaging, weighted averaging, and stacking. These techniques are popular methods to improve forecast accuracy and stability.

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