Interpolate missing values using a vital model

Uses a fitted vital model to interpolate missing values from a dataset.

Usage

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

Arguments

object

A mable containing a single model column.

new_data

A dataset with the same structure as the data used to fit the model.

...

Other arguments passed to interpolate methods.

Value

A vital object with missing values interpolated.

Author

Rob J Hyndman

Examples

nor_female <- norway_mortality |>
  dplyr::filter(Sex == "Female")
nor_female |>
  model(mean = FMEAN(Mortality)) |>
  interpolate(nor_female)
#> # A vital: 13,764 x 4 [1Y]
#> # Key:     Age x Sex [111 x 1]
#>     Year   Age Sex    Mortality
#>    <int> <int> <chr>      <dbl>
#>  1  1900     0 Female   0.0778 
#>  2  1900     1 Female   0.0290 
#>  3  1900     2 Female   0.0123 
#>  4  1900     3 Female   0.00786
#>  5  1900     4 Female   0.00624
#>  6  1900     5 Female   0.00538
#>  7  1900     6 Female   0.00422
#>  8  1900     7 Female   0.00376
#>  9  1900     8 Female   0.00380
#> 10  1900     9 Female   0.00365
#> # ℹ 13,754 more rows