| as_balanced | R Documentation |
This function corrects non-balanced input panel data by replacing missing entries with a user-given constant (e.g., 0).
as_balanced(
data,
col_cases,
col_date,
col_region,
fill_missing = 0
)
data |
|
col_cases |
Column containing the cases (numeric) |
col_date |
Column containing the time points (e.g., days) |
col_region |
Column containing the unique identifier of the regions (e.g., name, NUTS 3 code) |
fill_missing |
Constant to fill missing values (default and recommended: 0) |
The Swash-Backwash Model for the Single Epidemic Wave does not necessarily require balanced panel data in order for the calculations to be carried out. However, for a correct estimation it is implicitly assumed that the input data is balanced. The function corrects non-balanced panel data. It is executed automatically whithin the swash() function (when using the function is_balanced()), but can also be used separately.
data |
Corrected input dataset ( |
Thomas Wieland
is_balanced
data(COVID19Cases_geoRegion)
# Get SWISS COVID19 cases at NUTS 3 level
COVID19Cases_geoRegion <-
COVID19Cases_geoRegion[!COVID19Cases_geoRegion$geoRegion %in% c("CH", "CHFL"),]
# Exclude CH = Switzerland total and CHFL = Switzerland and Liechtenstein total
COVID19Cases_geoRegion <-
COVID19Cases_geoRegion[COVID19Cases_geoRegion$datum <= "2020-05-31",]
# Extract first COVID-19 wave
COVID19Cases_geoRegion_balanced <-
is_balanced(
data = COVID19Cases_geoRegion,
col_cases = "entries",
col_date = "datum",
col_region = "geoRegion"
)
# Test whether "COVID19Cases_geoRegion" is balanced panel data
COVID19Cases_geoRegion_balanced$data_balanced
# Balanced? TRUE or FALSE
if (COVID19Cases_geoRegion_balanced$data_balanced == FALSE) {
COVID19Cases_geoRegion <-
as_balanced(
COVID19Cases_geoRegion,
col_cases = "entries",
col_date = "datum",
col_region = "geoRegion"
)
}
# Correction of dataset "COVID19Cases_geoRegion"
# not necessary as parameter balance of is_balanced is set TRUE by default
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