This is a generic function to impute data from broader hierarchical geographical areas to smaller ones. It requires the exact specification of the of the geographical typology.
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
)An upstream data frame to project on containing smaller geographical units, for example, country-level data.
A downstream data frame containing the smaller level missing data observations. It must contain all the necessary structural information for imputation.
The geographical ID of the upstream data,
defaults to "country_code".
The geographical ID of the downstream data,
defaults to "geo_code".
The variable that contains the upstream data to be
imputed to the downstream data, defaults to "values".
The time component, if present, defaults to
"year".
The name of the variable that contains the
potentially applied imputation methods. Defaults to NULL.
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.
The more general impute_down function requires typology information from the higher
and lower level typologies. This is not needed when the EU vocabulary
is used, and the hierarchy can be established from the EU vocabularies.
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" )
}
#> geo_code year geo_name country_code my_var
#> 1 AU-NSW 2018 New South Wales state AU 10
#> 2 AU-QLD 2018 Queensland state AU 10
#> 3 AU-SA 2018 South Australia state AU 10
#> 4 AU-TAS 2018 Tasmania state AU 10
#> 5 AU-VIC 2018 Victoria state AU 10
#> 6 AU-WA 2018 Western Australia state AU 10
#> 7 AU-ACT 2018 Australian Capital Territory territory AU 10
#> 8 AU-NT 2018 Northern Territory territory AU 10
#> 9 AU-NSW 2019 New South Wales state AU 12
#> 10 AU-QLD 2019 Queensland state AU 12
#> 11 AU-SA 2019 South Australia state AU 12
#> 12 AU-TAS 2019 Tasmania state AU 12
#> 13 AU-VIC 2019 Victoria state AU 12
#> 14 AU-WA 2019 Western Australia state AU 12
#> 15 AU-ACT 2019 Australian Capital Territory territory AU 12
#> 16 AU-NT 2019 Northern Territory territory AU 12
#> 17 AU-NSW 2020 New South Wales state AU 11
#> 18 AU-QLD 2020 Queensland state AU 11
#> 19 AU-SA 2020 South Australia state AU 11
#> 20 AU-TAS 2020 Tasmania state AU 11
#> 21 AU-VIC 2020 Victoria state AU 11
#> 22 AU-WA 2020 Western Australia state AU 11
#> 23 AU-ACT 2020 Australian Capital Territory territory AU 11
#> 24 AU-NT 2020 Northern Territory territory AU 11
#> method description
#> 1 imputed from AU actual note1
#> 2 imputed from AU actual note1
#> 3 imputed from AU actual note1
#> 4 imputed from AU actual note1
#> 5 imputed from AU actual note1
#> 6 imputed from AU actual note1
#> 7 imputed from AU actual note1
#> 8 imputed from AU actual note1
#> 9 imputed from AU actual <NA>
#> 10 imputed from AU actual <NA>
#> 11 imputed from AU actual <NA>
#> 12 imputed from AU actual <NA>
#> 13 imputed from AU actual <NA>
#> 14 imputed from AU actual <NA>
#> 15 imputed from AU actual <NA>
#> 16 imputed from AU actual <NA>
#> 17 imputed from AU actual note3
#> 18 imputed from AU actual note3
#> 19 imputed from AU actual note3
#> 20 imputed from AU actual note3
#> 21 imputed from AU actual note3
#> 22 imputed from AU actual note3
#> 23 imputed from AU actual note3
#> 24 imputed from AU actual note3