_pkgdown.yml

template:
  params:
    bootswatch: flatly
    ganalytics: UA-76139189-2

navbar:
  title: "modeltime"
  left:
    - icon: fa-home
      href: index.html
    - text: "Getting Started"
      href: articles/getting-started-with-modeltime.html
    - text: "Articles"
      href: articles/index.html
      menu:
        - text: 'Forecasting'
        - text: 'Getting Started with Modeltime'
          href: articles/getting-started-with-modeltime.html
        - text: 'Autoregressive Forecasting (Recursive)'
          href: articles/recursive-forecasting.html
        - text: "---"
        - text: 'Algorithms'
        - text: 'Modeltime Base Algorithms'
          href: articles/modeltime-model-list.html
        - text: "---"
        - text: 'Developers'
        - text: 'Extending Modeltime (Developer Tools)'
          href: articles/extending-modeltime.html
    - text: "API"
      href: reference/index.html
      menu:
        - text: 'API Functions'
        - icon: fa-home
          text: 'Function Reference'
          href: reference/index.html
        - text: '---'
        - text: 'Change History'
        - text: "News"
          href: news/index.html
    - text: "Ecosystem"
      menu:
        - text: 'Forecast'
        - text: 'Modeltime (Forecasting)'
          href: https://business-science.github.io/modeltime/
        - text: 'TimeTK (Time Series Analysis)'
          href: https://business-science.github.io/timetk/
        - text: "---"
        - text: 'Improve'
        - text: 'Modeltime Ensemble (Blending Forecasts)'
          href: https://business-science.github.io/modeltime.ensemble/
        - text: 'Modeltime Resample (Backtesting)'
          href: https://business-science.github.io/modeltime.resample/
        - text: "---"
        - text: 'Scale'
        - text: 'Modeltime H2O (AutoML)'
          href: https://business-science.github.io/modeltime.h2o/
        - text: 'Modeltime GluonTS (Deep Learning)'
          href: https://business-science.github.io/modeltime.gluonts/
    - icon: fas fa-graduation-cap
      text: "Learn"
      href: https://university.business-science.io/p/ds4b-203-r-high-performance-time-series-forecasting/

  right:
    - icon: fab fa-github
      href: https://github.com/business-science/modeltime

reference:
  - title: Modeltime Workflow
    desc: The main workflow functions for scalable time series modeling.
  - subtitle: Core Functions
    contents:
    - modeltime_table
    - modeltime_calibrate
    - modeltime_forecast
    - modeltime_accuracy
    - modeltime_refit
  - subtitle: Recursive Forecast Prediction
    contents:
    - recursive
    - panel_tail
  - subtitle: Plotting & Tables
    contents:
    - starts_with("plot_modeltime")
    - starts_with("table_modeltime")
  - subtitle: Residual Analysis
    contents:
    - modeltime_residuals
    - modeltime_residuals_test
    - plot_modeltime_residuals
  - title: Algorithms
    desc: The `parsnip`-adjacent algorithms that implement time series models.
  - subtitle: Core Forecasting Methods
    contents:
    - prophet_reg
    - prophet_boost
    - arima_reg
    - arima_boost
    - exp_smoothing
    - seasonal_reg
    - nnetar_reg
  - subtitle: Baseline Algorithms (Simple Methods)
    contents:
    - window_reg
    - naive_reg
  - title: Modeltime Workflow Helpers
    contents:
    - combine_modeltime_tables
    - add_modeltime_model
    - update_modeltime_model
    - update_modeltime_description
    - pluck_modeltime_model
  - title: Accuracy Metrics (Yardstick)
    contents:
    - default_forecast_accuracy_metric_set
    - summarize_accuracy_metrics
    - metric_tweak
  - title: Parameters (Dials)
    desc: The `dials` parameter functions that support hyperparameter tuning with `tune`.
  - subtitle: General Time Series
    contents:
    - seasonal_period
  - subtitle: ARIMA
    contents:
    - starts_with("non_seasonal")
  - subtitle: Exponential Smoothing
    contents:
    - error
  - subtitle: Prophet
    contents:
    - changepoint_num
  - subtitle: NNETAR
    contents:
    - num_networks
  - title: Developer Tools
    desc: Tools for extending `modeltime`.
    contents:
    - new_modeltime_bridge
    - create_xreg_recipe
    - juice_xreg_recipe
    - parse_index_from_data
    - get_model_description
    - get_arima_description
  - title: Data
    contents:
    - starts_with("m750")

repo:
  url:
    home: https://github.com/business-science/modeltime
    source: https://github.com/business-science/modeltime/blob/master/
    issue: https://github.com/business-science/modeltime/issues/