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Generate point nowcast

Source: R/fill_triangles.R
fill_triangle.Rd

This function ingests a reporting triangle matrix and optionally, a delay distribution, and returns a completed reporting square which represents the point nowcast. If a delay distribution is specified, this will be used to generate the nowcast, otherwise, a delay distribution will be estimated from the reporting_triangle.

Usage

fill_triangle(
  reporting_triangle,
  n = nrow(reporting_triangle),
  delay_pmf = NULL,
  validate = TRUE
)

Arguments

reporting_triangle

A reporting_triangle object with rows representing reference times and columns representing delays. Can be a reporting matrix or incomplete reporting matrix. Can also be a ragged reporting triangle, where multiple columns are reported for the same row (e.g., weekly reporting of daily data).

n

Integer indicating the number of reference times (observations) to be used in the estimate of the reporting delay, always starting from the most recent reporting delay. The default is to use the whole reporting triangle, so nrow(reporting_triangle).

delay_pmf

Vector of delays assumed to be indexed starting at the first delay column in reporting_triangle. Default is NULL, which will estimate a delay from the reporting_triangle.

validate

Logical. If TRUE (default), validates the object. Set to FALSE only when called from functions that already validated.

Value

point_nowcast_matrix Matrix of the same number of rows and columns as the reporting_triangle but with the missing values filled in as point estimates.

See also

Point nowcast generation functions apply_delay(), fill_triangles()

Examples

# Fill triangle using default delay estimation
point_nowcast_matrix <- fill_triangle(
  reporting_triangle = example_reporting_triangle
)
point_nowcast_matrix
#> Reporting Triangle
#> ℹ The reporting triangle does not contain any missing values.
#> Delays unit: days
#> Reference dates: 2024-01-01 to 2024-01-05
#> Max delay: 3
#> Structure: 0
#> 
#>              0        1        2        3
#> 2024-01-01  80 50.00000 25.00000 10.00000
#> 2024-01-02 100 50.00000 20.00000 10.97165
#> 2024-01-03  90 45.00000 21.72707 10.11533
#> 2024-01-04 110 59.32834 27.24413 12.68600
#> 2024-01-05  95 51.27278 23.53877 10.95949