Generate multiple draws of a nowcast combining observed and predicted values

Usage

get_nowcast_draws(
  point_nowcast_matrix,
  reporting_triangle,
  dispersion,
  draws = 1000,
  ...
)

Arguments

point_nowcast_matrix: Matrix of point nowcast predictions and observations, with rows representing the reference times and columns representing the delays.
reporting_triangle: Matrix of the reporting triangle, with rows representing the time points of reference and columns representing the 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).
dispersion: Vector of dispersion parameters indexed by horizon from minus one to the maximum delay.
draws: Integer indicating the number of draws of the predicted nowcast vector to generate. Default is 1000.
...: Additional arguments pass to get_nowcast_pred_draws()

Value

Dataframe containing information for multiple draws with columns for the reference time (time), the predicted counts (pred_count), and the draw number (draw).

Examples

point_nowcast_matrix <- matrix(
  c(
    80, 50, 25, 10,
    100, 50, 30, 20,
    90, 45, 25, 16.8,
    80, 40, 21.2, 19.5,
    70, 34.5, 15.4, 9.1
  ),
  nrow = 5,
  byrow = TRUE
)
reporting_triangle <- generate_triangle(point_nowcast_matrix)
disp <- c(0.8, 12.4, 9.1)
nowcast_draws <- get_nowcast_draws(
  point_nowcast_matrix,
  reporting_triangle,
  disp,
  draws = 5
)
nowcast_draws
#>    pred_count time draw
#> 1         165    1    1
#> 2         200    2    1
#> 3         170    3    1
#> 4         148    4    1
#> 5          73    5    1
#> 6         165    1    2
#> 7         200    2    2
#> 8         175    3    2
#> 9         168    4    2
#> 10         85    5    2
#> 11        165    1    3
#> 12        200    2    3
#> 13        181    3    3
#> 14        187    4    3
#> 15         78    5    3
#> 16        165    1    4
#> 17        200    2    4
#> 18        173    3    4
#> 19        180    4    4
#> 20         95    5    4
#> 21        165    1    5
#> 22        200    2    5
#> 23        169    3    5
#> 24        151    4    5
#> 25        211    5    5