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Build a csfmt_reporting_triangle_v3

Source: R/csfmt_reporting_triangle_v3.R
csfmt_reporting_triangle_v3.Rd

Builds the input of the nowcast engines: counts by reference ISO week and by the date each count was reported. The newest reporting date is the as-of boundary.

Usage

csfmt_reporting_triangle_v3(
  data,
  id_cols,
  reference_col = "isoyearweek_reference",
  reporting_col = "reporting_date",
  value_col = "numerator"
)

Arguments

data

A data.table with the identity, reference, reporting and count columns.

id_cols

The identity columns that define one series.

reference_col

The reference ISO-week column, written "YYYY-WW".

reporting_col

The column with the date each count was reported. Its class MUST be exactly Date, so an IDate is an error. It MUST NOT hold NA. One NA would make the as-of boundary NA. Every nowcast engine would then return the observed totals with no warning.

value_col

The count column.

Value

A csfmt_reporting_triangle_v3: a data.table with the attributes as_of, a Date, and id_cols, reference_col, reporting_col and value_col.

Details

The triangle is sparse. An absent cell on or before the as-of date is a zero, and a cell after it is not reported yet. The constructor copies data and adds the ids of set_time_series_id(). It stops with an error when a reporting date comes before its reference Monday, or a count is negative.

See also

vignette("pipeline", package = "csalert"), which takes a triangle through the whole pipeline.

Other reporting triangle functions: isoyearweek_week_start(), reporting_triangle_matrix()

Examples

# 40 reference weeks, each reported 3, 10 and 17 days after its Monday. The
# data stops at one as-of date, so the newest weeks are still incomplete.
cal <- cstime::dates_by_isoyearweek
i <- match("2023-01", cal$isoyearweek)
set.seed(1)
monday <- as.Date(cal$mon[i + rep(0:39, each = 3)])
d <- data.table::data.table(
  isoyearweek_reference = cal$isoyearweek[i + rep(0:39, each = 3)],
  reporting_date = monday + rep(c(3, 10, 17), 40),
  numerator = rpois(120, c(30, 15, 5)),
  indicator_tag = "x", location_code = "nation", age = "total", sex = "total"
)
d <- d[reporting_date <= as.Date(cal$mon[i + 39]) + 6]

tri <- csfmt_reporting_triangle_v3(
  d,
  id_cols = c("indicator_tag", "location_code", "age", "sex")
)

# the as-of boundary is the newest reporting date in the data
attr(tri, "as_of")
#> [1] "2023-10-05"
head(tri, 3)
#>    isoyearweek_reference reporting_date numerator indicator_tag location_code
#>                   <char>         <Date>     <int>        <char>        <char>
#> 1:               2023-01     2023-01-05        26             x        nation
#> 2:               2023-01     2023-01-12        20             x        nation
#> 3:               2023-01     2023-01-19         8             x        nation
#>       age    sex   time_series_id             time_series_label
#>    <char> <char>           <char>                        <char>
#> 1:  total  total d8da72e3fbb5fd29 x\037nation\037total\037total
#> 2:  total  total d8da72e3fbb5fd29 x\037nation\037total\037total
#> 3:  total  total d8da72e3fbb5fd29 x\037nation\037total\037total