Aggregate univariate or multivariate time series from low to high frequency

Usage

aggr(x, conv_type = "mean", target_freq = "year", na_rm = FALSE)

Arguments

x: a tx-boxable object at a high frequency (e.g. monthly or quarterly)
conv_type: match the aggregated value via "first", "last", "sum", "mean". If conv_type == "uhero" then the name of the time series x is compared to the internal variable sum_pattern. For matching series names the aggregation is based on "sum"; for all others it is based on "mean."
target_freq: target frequency "year", "quarter", "month", "week"
na_rm: logical, if TRUE, incomplete periods are aggregated as well. For irregular series, incomplete periods are always aggregated.

Value

aggregated object of the same type as the input

Examples

monthly_data_example |>
  aggr(conv_type = "sum", target_freq = "quarter")
#> # A tibble: 98 × 4
#>    time       VISNS_HI VAPNS_HI VADCNS_HI
#>    <date>        <dbl>    <dbl>     <dbl>
#>  1 2000-10-01    1686.    1797.      487.
#>  2 2001-01-01    1730.    1774.      531.
#>  3 2001-04-01    1683.    1853.      479.
#>  4 2001-07-01    1650.    1835.      486.
#>  5 2001-10-01    1287.    1440.      402.
#>  6 2002-01-01    1558.    1655.      489.
#>  7 2002-04-01    1600.    1773.      460.
#>  8 2002-07-01    1701.    1900.      502.
#>  9 2002-10-01    1594.    1765.      471.
#> 10 2003-01-01    1580.    1730.      491.
#> # ℹ 88 more rows
monthly_data_example |>
  aggr(conv_type = "uhero", target_freq = "quarter")
#> # A tibble: 98 × 4
#>    time       VISNS_HI VAPNS_HI VADCNS_HI
#>    <date>        <dbl>    <dbl>     <dbl>
#>  1 2000-10-01    1686.    1797.      162.
#>  2 2001-01-01    1730.    1774.      177.
#>  3 2001-04-01    1683.    1853.      160.
#>  4 2001-07-01    1650.    1835.      162.
#>  5 2001-10-01    1287.    1440.      134.
#>  6 2002-01-01    1558.    1655.      163.
#>  7 2002-04-01    1600.    1773.      153.
#>  8 2002-07-01    1701.    1900.      167.
#>  9 2002-10-01    1594.    1765.      157.
#> 10 2003-01-01    1580.    1730.      164.
#> # ℹ 88 more rows
monthly_data_example |>
  aggr(conv_type = "uhero", target_freq = "quarter") |>
  tsbox::ts_long() |>
  disagg(conv_type = "uhero", target_freq = "month") |>
  tsbox::ts_wide() # this is close to original data
#> # A tibble: 294 × 4
#>    time       VISNS_HI VAPNS_HI VADCNS_HI
#>    <date>        <dbl>    <dbl>     <dbl>
#>  1 2000-10-01     558.     602.      158.
#>  2 2000-11-01     561.     600.      161.
#>  3 2000-12-01     567.     596.      168.
#>  4 2001-01-01     577.     590.      177.
#>  5 2001-02-01     579.     589.      179.
#>  6 2001-03-01     574.     595.      175.
#>  7 2001-04-01     562.     607.      163.
#>  8 2001-05-01     558.     618.      158.
#>  9 2001-06-01     563.     629.      159.
#> 10 2001-07-01     575.     639.      166.
#> # ℹ 284 more rows
# works with a single series too
monthly_data_example |>
  tsbox::ts_long() |>
  tsbox::ts_pick("VISNS_HI") |>
  aggr(conv_type = "uhero", target_freq = "year") |>
  tsbox::ts_plot()