impute_down: Imputing Data From Larger To Smaller Units
In regions: Processing Regional Statistics

Description Usage Arguments Value See Also Examples

Imputing Data From Larger To Smaller Units

impute_down(
  upstream_data = NULL,
  downstream_data = NULL,
  country_var = "country_code",
  regional_code = "geo_code",
  values_var = "values",
  time_var = NULL,
  upstream_method_var = NULL,
  downstream_method_var = NULL
)

`upstream_data`	An upstream data frame to project on containing smaller geographical units, for example, country-level data.
`downstream_data`	A downstream data frame containing the smaller level missing data observations. It must contain all the necessary structural information for imputation.
`country_var`	The geographical ID of the upstream data, defaults to `"country_code"`.
`regional_code`	The geographical ID of the downstream data, defaults to `"geo_code"`.
`values_var`	The variable that contains the upstream data to be imputed to the downstream data, defaults to `"values"`.
`time_var`	The time component, if present, defaults to `"year"`.
`upstream_method_var`	The name of the variable that contains the potentially applied imputation methods. Defaults to `NULL`.
`downstream_method_var`	The name of the variable that will contain the metadata of the potentially applied imputation methods. Defaults to `NULL` in which case a variable called `'method'` will be created. If possible, avoid using `upstream_data` or `downstream_data` that contains a variable called `'method'` for other purposes.

The upstream data frame (containing data of a larger unit) and the downstream data (containing data of smaller sub-divisional units) are joined; whenever data is missing in the downstream sub-divisional column, it is imputed with the corresponding values from the upstream data frame. The 'method' metadata column explains if the actual downstream data or the imputed data can be found in the downstream value column.

Other impute functions: impute_down_nuts()

{
upstream <- data.frame ( country_code =  rep( "AU", 3),
                         year = c(2018:2020),
                         my_var  = c(10,12,11),
                         description = c("note1", NA_character_,
                         "note3")
                       )

downstream <- australia_states

impute_down ( upstream_data  = upstream,
              downstream_data = downstream,
              country_var = "country_code",
              regional_code = "geo_code",
              values_var = "my_var",
              time_var = "year" )
}