Plot the transport-discriminant plane

Places each report date by its creation score (x) and transport / deficit score (y) from transport_discriminant(), shading the region that decides the batch call. Surges are not distinguished here (they fold into the quiet background) since only the batch call is of interest.

Usage

plot_transport_discriminant(
  x,
  ...,
  plotly = FALSE,
  size = 1,
  grid_linewidth = 0.3,
  palette = .tbl_now_palette()
)

Arguments

x

A tbl_now() object.

...

Passed to transport_discriminant() (e.g. lookback, period, alpha).

plotly

If TRUE, return an interactive plotly widget instead of a static plot. Default FALSE.

size

Multiplier on the size of the points and their date labels. Default 1: unflagged points are drawn at 1.1, confirmed batches at 2.6. It is a multiplier rather than an absolute size precisely so that enlarging the marks keeps the flagged ones bigger than the rest.

grid_linewidth

Line width of the zero lines and the dashed significance thresholds this function draws – the package's own reference grid, not ggplot2's. Default 0.3.

palette

A named colour palette (see tbl_now_palette()).

Value

A ggplot2 object (or a plotly widget when plotly = TRUE).

Details

Only the diagnose_batches()-confirmed batches (Benjamini-Hochberg-corrected) are coloured red; the dashed lines and shaded region are a reference for where a batch sits (deficit cleared, and significant), not the flagging rule. The most extreme-looking points (far left, far up) are holds – windows still depleted because the release has not happened yet – not batches. A genuine batch sits in the band just to the right of the vertical line, once the window total recovers.

See also

transport_discriminant() for the numbers behind the plane; diagnose_batches() for the hypothesis test that flags the red points; plot_reporting_process() for the series they come from; diagnostic_plot() for the whole gallery.

Examples

data(denguedat)
# The two and a half years around the 1996 and 1997 backlog dumps, so that
# the plane has red points on it without scanning the whole series.
window <- denguedat[
  denguedat$onset_week >= as.Date("1995-06-01") &
    denguedat$onset_week <= as.Date("1998-01-01"),
]
dn <- tbl_now(window, onset_week, report_week, verbose = FALSE)
plot_transport_discriminant(dn)