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Snapshots of one series, as EpiNow2 estimates truncation from

tbl_now_epinow2_snapshots.Rd

[Experimental]

The object returned by tbl_now_to_EpiNow2(x, target = "estimate_truncation"): a list of date/confirm data frames, one per report date, plus the report dates themselves so the object can be turned back into a tbl_now.

It is a thin class – still a list, so it can be handed to EpiNow2::estimate_truncation() unchanged:

snaps <- tbl_now_to_EpiNow2(x, target = "estimate_truncation")
EpiNow2::estimate_truncation(snaps)

The class exists because a bare list of date/confirm frames does not say when each snapshot was taken, and without that the reporting triangle cannot be recovered from it. Printing also distinguishes it from the superficially similar list EpiNow2::estimate_secondary() does not take.

Usage

# S3 method for class 'tbl_now_epinow2_snapshots'
print(x, ...)

Arguments

x

A tbl_now_epinow2_snapshots.

...

Ignored.

Value

print() returns x invisibly.

See also

tbl_now_to_EpiNow2(), as_tbl_now()

Examples

data(denguedat)
dengue <- tbl_now(denguedat[1:3000, ],
  event_date = onset_week, report_date = report_week, verbose = FALSE
)

# A stack of snapshots: what the series looked like at each of several past
## report dates. EpiNow2::estimate_truncation() uses these to learn how much
# the most recent counts are still going to grow.
snaps <- tbl_now_to_EpiNow2(dengue,
  target = "estimate_truncation", verbose = FALSE, quiet = TRUE
)

# Printing summarises the stack rather than dumping every snapshot.
snaps
#> ── 5 reporting snapshots from a <tbl_now> ──────────────────────────────────────
#> • One per report date: "1991-09-02", "1991-09-09", "1991-09-16", "1991-09-23", and "1991-10-14"
#> • Rows each: 602, 602, 602, 602, and 602
#> • Now: "1991-10-14"
#> ℹ Pass this to `EpiNow2::estimate_truncation()`. `EpiNow2::estimate_secondary()` wants a single data frame of linked series instead -- not this.

length(snaps)
#> [1] 5
head(snaps[[1]])
#>         date confirm accumulate
#> 1 1989-12-26      NA       TRUE
#> 2 1989-12-27      NA       TRUE
#> 3 1989-12-28      NA       TRUE
#> 4 1989-12-29      NA       TRUE
#> 5 1989-12-30      NA       TRUE
#> 6 1989-12-31      NA       TRUE