Smooth population counts in 5-year age groups using the Carrier-Farrag, Karup-King-Newton, Arriaga, United Nations, Strong, MAV or Zigzag methods. Allows for imputation of values in the youngest and oldest age groups for the Carrier-Farrag, Karup-King-Newton, and United Nations methods.
Input data. UN format.
character string. Options include "Carrier-Farrag","Arriaga","KKN","United Nations", "Strong", MAV and "Zigzag". See details. Default "Carrier-Farrag".
integer. The lowest age included included in intermediate adjustment. Default 10. Only relevant for Strong method.
integer. The highest age class included in intermediate adjustment. Default 65. Only relevant for Strong method.
integer. The width of the moving average. Default 3 intervals (x-5 to x+9). Only relevant for moving average method.
NA or character. Method to use for ages 0-9. See details. Default "original".
NA or character. Method to use for the final age groups. See details. Default "original".
Logical value. If TRUE messages are printed
as the method is applied. Set verbose = FALSE to silent the function.
Other arguments to be passed on to other methods and functions.
A data.frame having the same number of columns as input data. Different numbers of rows. UN format.
The Carrier-Farrag, Karup-King-Newton (KKN), and Arriaga methods do not modify the totals in each 10-year age group, whereas the United Nations, Strong, Zigzag, and moving average (MAV) methods do. The age intervals of input data could be any integer structure (single, abridged, 5-year, other), but output is always in 5-year age groups. All methods except the United Nations and MAV methods operate based on 10-year age group totals, excluding the open age group.
The Carrier-Farrag, Karup-King-Newton, and United Nations methods do not produce estimates
for the first and final 10-year age groups. By default, these are imputed with the original 5-year age group totals, but
you can also specify to impute with NA, or the results of the Arriaga,
Strong and Cascade methods. If the terminal digit of the open age group is 5, then the terminal 10-year
age group shifts down, so imputations may affect more ages in this case. Imputation can follow
different methods for young and old ages.
Method names are simplified using simplify.text and checked against a set of plausible matches
designed to give some flexibility in case you're not sure
In accordance with the description of these methods in Arriaga (1994), it is advised to compare the results from a variety of methods.
P5 <- DDSQLtools.data$Pop5_Egypt_M_DB
M <- c("Carrier-Farrag", "KKN", "Arriaga",
"United Nations", "Strong", "Zigzag", "MAV")
S1 <- do_smoothing(P5, method = M[1])
S2 <- do_smoothing(P5, method = M[2])
S3 <- do_smoothing(P5, method = M[3])
S4 <- do_smoothing(P5, method = M[4])
S5 <- do_smoothing(P5, method = M[5])
S6 <- do_smoothing(P5, method = M[6])
S7 <- do_smoothing(P5, method = M[7])
select_columns <- c("AgeID", "AgeStart", "AgeMid", "AgeEnd", "AgeLabel",
"DataTypeName", "DataTypeID", "DataValue")
S1[, select_columns]
#> # A tibble: 16 × 8
#> AgeID AgeStart AgeMid AgeEnd AgeLabel DataTypeName DataTypeID DataValue
#> <lgl> <dbl> <dbl> <dbl> <fct> <chr> <chr> <dbl>
#> 1 NA 0 2.5 5 0-4 DemoTools::age… do_smoothing… 3951843
#> 2 NA 5 7.5 10 5-9 DemoTools::age… do_smoothing… 3936424
#> 3 NA 10 12.5 15 10-14 DemoTools::age… do_smoothing… 4234663.
#> 4 NA 15 17.5 20 15-19 DemoTools::age… do_smoothing… 4132916.
#> 5 NA 20 22.5 25 20-24 DemoTools::age… do_smoothing… 3835300.
#> 6 NA 25 27.5 30 25-29 DemoTools::age… do_smoothing… 3321728.
#> 7 NA 30 32.5 35 30-34 DemoTools::age… do_smoothing… 2529984.
#> 8 NA 35 37.5 40 35-39 DemoTools::age… do_smoothing… 2178255.
#> 9 NA 40 42.5 45 40-44 DemoTools::age… do_smoothing… 2098388.
#> 10 NA 45 47.5 50 45-49 DemoTools::age… do_smoothing… 1834366.
#> 11 NA 50 52.5 55 50-54 DemoTools::age… do_smoothing… 1535701.
#> 12 NA 55 57.5 60 55-59 DemoTools::age… do_smoothing… 1213834.
#> 13 NA 60 62.5 65 60-64 DemoTools::age… do_smoothing… 896041
#> 14 NA 65 67.5 70 65-69 DemoTools::age… do_smoothing… 638954
#> 15 NA 70 72.5 75 70-74 DemoTools::age… do_smoothing… 401297
#> 16 NA 75 87.5 0 75+ DemoTools::age… do_smoothing… 375648
S <- cbind(S1$DataValue, S2$DataValue, S3$DataValue,
S4$DataValue, S5$DataValue, S6$DataValue, S7$DataValue)
dimnames(S) <- list(Age = S1$AgeLabel, SmoothingMethod = M)
S
#> SmoothingMethod
#> Age Carrier-Farrag KKN Arriaga United Nations Strong Zigzag
#> 0-4 3951843 3951843 3813809 3951843 3868225.4 3951843.0
#> 5-9 3936424 3936424 4074458 3936424 4020041.6 3936424.0
#> 10-14 4234663 4229492 4264697 4076626 4118061.1 4053592.3
#> 15-19 4132916 4138087 4102882 4292026 3947097.2 4256199.5
#> 20-24 3835300 3807223 3833019 3986911 3667466.1 4046477.2
#> 25-29 3321728 3349805 3324009 3152875 3283462.8 3192630.1
#> 30-34 2529984 2555637 2520776 2485954 2784409.8 2443296.8
#> 35-39 2178255 2152602 2187463 2241969 2419614.0 2179786.3
#> 40-44 2098388 2088796 2097290 2084947 2091286.8 2113598.4
#> 45-49 1834366 1843958 1835464 1850159 1797414.7 1888536.9
#> 50-54 1535701 1524627 1525280 1547446 1539709.0 1537081.2
#> 55-59 1213834 1224908 1224255 1208549 1243421.0 1197050.7
#> 60-64 896041 896041 920620 901219 937185.4 902926.7
#> 65-69 638954 638954 614375 638954 621002.3 638954.0
#> 70-74 401297 401297 401297 401297 401297.0 401297.0
#> 75+ 375648 375648 375648 375648 375648.0 375648.0
#> SmoothingMethod
#> Age MAV
#> 0-4 3951843.0
#> 5-9 3961357.3
#> 10-14 4101334.3
#> 15-19 4126853.7
#> 20-24 3842934.0
#> 25-29 3187917.7
#> 30-34 2617428.3
#> 35-39 2256497.0
#> 40-44 2078089.3
#> 45-49 1823822.3
#> 50-54 1540345.7
#> 55-59 1215192.0
#> 60-64 915272.3
#> 65-69 645430.7
#> 70-74 401297.0
#> 75+ 375648.0