R: Tidy forecast objects

sw_sweep {sweep} | R Documentation

## Tidy forecast objects

### Description

Tidy forecast objects

### Usage

    sw_sweep(x, fitted = FALSE, timetk_idx = FALSE, rename_index = "index", ...)

### Arguments

`x` | A time-series forecast of class `forecast`.
`fitted` | Whether or not to return the fitted values (model values) in the results. FALSE by default.
`timetk_idx` | If timetk index (non-regularized index) is present, uses it to develop forecast. Otherwise uses default index.
`rename_index` | Enables the index column to be renamed.
`...` | Additional arguments passed to `tk_make_future_timeseries()`

### Details

`sw_sweep` is designed to coerce `forecast` objects from the `forecast` package into `tibble` objects in a "tidy" format (long). The returned object contains both the actual values and the forecasted values including the point forecast and upper and lower confidence intervals.

The `timetk_idx` argument is used to modify the return format of the index.

- If `timetk_idx = FALSE`, a regularized time index is always constructed. This may be in the format of numeric values (e.g. 2010.000) or the higher order `yearmon` and `yearqtr` classes from the `zoo` package. A higher order class is attempted to be returned.

- If `timetk_idx = TRUE` and a timetk index is present, an irregular time index will be returned that combines the original time series (i.e. date or datetime) along with a computed future time series created using `tk_make_future_timeseries()` from the `timetk` package. The `...` can be used to pass additional arguments to `tk_make_future_timeseries()` such as `inspect_weekdays`, `skip_values`, etc that can be useful in tuning the future time series sequence.

The index column name can be changed using the `rename_index` argument.

### Value

Returns a `tibble` object.

### See Also

`tk_make_future_timeseries()`

### Examples

    library(forecast)
    library(sweep)
    library(dplyr)

    # ETS forecasts
    USAccDeaths %>%
        ets() %>%
        forecast(level = c(80, 95, 99)) %>%
        sw_sweep()

[Package sweep version 0.2.3 Index]