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Add a rate to an ensemble

Source: R/rate.R
ens_add_rate.Rd

Divides one draw matrix by another, draw by draw, and adds the result as a new draw matrix. Column j is the same draw in every measure, so the rate carries the uncertainty of both.

Usage

ens_add_rate(x, ...)

# S3 method for class 'csfmt_ensemble_v3'
ens_add_rate(x, numerator, denominator, per = 100, name = NULL, ...)

Arguments

x

The csfmt_ensemble_v3 that holds both measures.

...

Passed to the method.

numerator, denominator

Two draw matrices in $draws.

per

The scale of the rate. 100 gives a percentage.

name

The name of the new measure. NULL uses csfmt_var(numerator, denom = denominator, per = per).

Value

x with the rate in $draws.

Details

A zero denominator gives NA, not 0. The rate is capped at per, because the numerator is a subset of the denominator, and a draw above the cap gives a warning.

See also

vignette("pipeline", package = "csalert"), stage 4.

Other ensemble operations: ens_collapse(), mem_thresholds_v1(), short_term_trend(), signal_detection_hlm()

Examples

d <- data.table::data.table(
  location_code = "nation",
  age = "total",
  isoyearweek = c("2023-01", "2023-02", "2023-03")
)
# The numerator is a SUBSET of the denominator: positive tests out of tests
# taken. So simulate the denominator first, and the numerator from it.
set.seed(1)
denom <- matrix(rpois(3 * 100, 200), nrow = 3)
numer <- matrix(rbinom(length(denom), size = denom, prob = 0.10), nrow = 3)
ens <- csfmt_ensemble_v3(
  d,
  id_cols = c("location_code", "age"),
  draws = list(
    numerator_nowcasted = numer,
    denominator_nowcasted = denom
  )
)

ens <- ens_add_rate(
  ens,
  numerator = "numerator_nowcasted",
  denominator = "denominator_nowcasted",
  per = 100
)

# the rate is a third draw matrix, named by the grammar
names(ens$draws)
#> [1] "numerator_nowcasted"                               
#> [2] "denominator_nowcasted"                             
#> [3] "numerator_nowcasted_vs_denominator_nowcasted_pr100"

# its interval carries the uncertainty of both measures
r <- ens_collapse(ens, probs = c(0.05, 0.5, 0.95))
r[, .(
  isoyearweek,
  lo = numerator_nowcasted_vs_denominator_nowcasted_pr100_q05x0,
  med = numerator_nowcasted_vs_denominator_nowcasted_pr100_q50x0,
  hi = numerator_nowcasted_vs_denominator_nowcasted_pr100_q95x0
)]
#>    isoyearweek       lo      med       hi
#>         <char>    <num>    <num>    <num>
#> 1:     2023-01 7.115385 9.755516 14.31502
#> 2:     2023-02 5.699153 9.867335 13.52267
#> 3:     2023-03 6.371382 9.476179 13.27110