plot.forecastML: Plot an object of class 'forecastML'
In nredell/forecastML: Time Series Forecasting with Machine Learning Methods

A forecast plot of h-step-ahead forecasts produced from multiple horizon-specific forecast models using combine_forecasts().

## S3 method for class 'forecastML'
plot(
  x,
  data_actual = NULL,
  actual_indices = NULL,
  facet = ~model,
  models = NULL,
  group_filter = NULL,
  drop_facet = FALSE,
  interval_fill = NULL,
  interval_alpha = NULL,
  ...
)

`x`	An object of class 'forecastML' from `combine_forecasts()`.
`data_actual`	A data.frame containing the target/outcome name and any grouping columns. The data can be historical actuals and/or holdout/test data.
`actual_indices`	Required if `data_actual` is given. A vector or 1-column data.frame of numeric row indices or dates (class 'Date' or 'POSIXt') with length `nrow(data_actual)`. The data can be historical actuals and/or holdout/test data.
`facet`	Optional. A formula with any combination of `model`, or `group` (for grouped time series) passed to `ggplot2::facet_grid()` internally (e.g., `~ model`, `model ~ .`, `~ model + group`).
`models`	Optional. Filter results by user-defined model name from `train_model()`.
`group_filter`	Optional. A string for filtering plot results for grouped time-series (e.g., `"group_col_1 == 'A'"`); passed to `dplyr::filter()` internally.
`drop_facet`	Optional. Boolean. If actuals are given when forecasting factors, the plot facet with 'actual' data can be dropped.
`interval_fill`	A character vector of color names or hex codes to fill the prediction intervals. For intervals with multiple levels, the first color corresponds to the fill with the widest interval.
`interval_alpha`	A numeric vector of alpha values to shade the prediction intervals. For intervals with multiple levels, the first value corresponds to the shading with the widest interval.
`...`	Not used.