R: Interpolate missing values from a fable model

interpolate.ARIMA {fable} | R Documentation

## Interpolate missing values from a fable model

### Description

Applies a model-specific estimation technique to predict the values of missing values in a `tsibble`, and replace them.

### Usage

    ## S3 method for class 'ARIMA'
    interpolate(object, new_data, specials, ...)

### Arguments

`object` | The time series model used to produce the forecasts
`new_data` | A `tsibble` containing future information used to forecast.
`specials` | (passed by `fabletools::forecast.mdl_df()`).
`...` | Additional arguments for forecast model methods.

### Value

A tibble of the same dimension of `new_data` with missing values interpolated.

### Examples

    library(tsibbledata)

    olympic_running %>%
      model(arima = ARIMA(Time ~ trend())) %>%
      interpolate(olympic_running)

[Package fable version 0.3.1 Index]