Aggregates mortality data to a weekly basis. Where the percentiles and number of deaths obtained after every week up to n_week is also given. For more details see the help vignette:
Arguments
- data
Dataset containing doe (Date of event), dor (Date of registation) and location_code. The columns must have these exact names.
- aggregation_date
Date of aggregation
- n_week
Number of weeks to calculate the percentage of the total registraations. Must be larger og equal to 2 amd smaller than the total number of weeks in the dataset.
- pop_data
Population data, must contain a column called pop with the population data and a column with year and possibly week.
Examples
data <- nowcast::data_fake_nowcasting_raw
data[doe < as.Date("2019-01-01")]
#> doe dor location_code
#> 1: 2018-01-01 2018-01-10 norge
#> 2: 2018-01-01 2018-01-07 norge
#> 3: 2018-01-01 2018-01-05 norge
#> 4: 2018-01-01 2018-01-07 norge
#> 5: 2018-01-01 2018-01-05 norge
#> ---
#> 42115: 2018-12-31 2019-01-08 norge
#> 42116: 2018-12-31 2019-01-11 norge
#> 42117: 2018-12-31 2019-01-06 norge
#> 42118: 2018-12-31 2019-01-04 norge
#> 42119: 2018-12-31 2019-01-05 norge
aggregation_date <- as.Date("2020-01-01")
n_week <- 6
data_aggregated <- nowcast_aggregate(data, aggregation_date, n_week)
#> 1 done
#> 2 done
#> 3 done
#> 4 done
#> 5 done
#> 6 done