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

act_female <- aus_mortality |>
 dplyr::filter(Code == "ACTOT", Sex == "female")
act_female |>
 model(mean = FMEAN(Mortality)) |>
 interpolate(act_female)
#> # A vital: 10,403 x 6 [1Y]
#> # Key:     Age x (Sex, State, Code) [101 x 1]
#>     Year   Age Sex    State                                      Code  Mortality
#>    <int> <int> <chr>  <chr>                                      <chr>     <dbl>
#>  1  1901     0 female Australian Capital Territory and Overseas… ACTOT         0
#>  2  1901     1 female Australian Capital Territory and Overseas… ACTOT         0
#>  3  1901     2 female Australian Capital Territory and Overseas… ACTOT         0
#>  4  1901     3 female Australian Capital Territory and Overseas… ACTOT         0
#>  5  1901     4 female Australian Capital Territory and Overseas… ACTOT         0
#>  6  1901     5 female Australian Capital Territory and Overseas… ACTOT         0
#>  7  1901     6 female Australian Capital Territory and Overseas… ACTOT         0
#>  8  1901     7 female Australian Capital Territory and Overseas… ACTOT         0
#>  9  1901     8 female Australian Capital Territory and Overseas… ACTOT         0
#> 10  1901     9 female Australian Capital Territory and Overseas… ACTOT         0
#> # ℹ 10,393 more rows