
Default quantile levels for a nowcast
nowcast_quantile_levels.RdThe quantile levels run_nowcast() summarises a nowcast at by default: nine
probabilities, symmetric about the median, spanning the 50%, 80%, 90% and 95%
central intervals.
They are a subset of the 23 levels the US and European COVID-19 forecast
hubs and FluSight ask for (0.01, 0.025, 0.05, then 0.10 to 0.90 in steps of
0.05, then 0.975 and 0.99). Nine cover the intervals people actually read at a
fraction of the storage, and every one of them is a hub level, so the output
still scores against hub submissions in scoringutils without
interpolation. Pass quantile_levels explicitly when you need the full hub
set:
hub_levels <- c(0.01, 0.025, seq(0.05, 0.95, by = 0.05), 0.975, 0.99)
run_nowcast(x, engine("baselinenowcast", quantile_levels = hub_levels))The levels live on the engine(), not on run_nowcast(), because for some
backends they are a fit-time model argument rather than a way of summarising
afterwards.
Backends that expose draws can honour any levels you ask for. Ones that report
a point estimate and a single interval ("surveillance", "EpiNow2") cannot,
and say so rather than interpolating.
See also
engine(), whose quantile_levels argument this is the default for;
run_nowcast() and nowcast_backtest(), which report at these levels;
score_nowcast() and as_scoringutils(), which score them.
Examples
nowcast_quantile_levels()
#> [1] 0.025 0.050 0.100 0.250 0.500 0.750 0.900 0.950 0.975
# The 50%, 80%, 90% and 95% central intervals, as lower/upper pairs.
matrix(nowcast_quantile_levels()[-5], ncol = 2)
#> [,1] [,2]
#> [1,] 0.025 0.750
#> [2,] 0.050 0.900
#> [3,] 0.100 0.950
#> [4,] 0.250 0.975
# Ask an engine for something else -- here the full forecast-hub set.
hub_levels <- c(0.01, 0.025, seq(0.05, 0.95, by = 0.05), 0.975, 0.99)
engine("baselinenowcast", quantile_levels = hub_levels)
#> ── <nowcast_engine: "baselinenowcast"> ─────────────────────────────────────────
#> • quantile levels: 0.01, 0.025, 0.05, 0.1, 0.15, 0.2, 0.25, 0.3, 0.35, 0.4, 0.45, 0.5, 0.55, 0.6, 0.65, 0.7, 0.75, 0.8, …, 0.975, and 0.99