report_cases | R Documentation |
Convolves latent infections to reported cases via an observation model.
Likely to be removed/replaced in later releases by functionality drawing on
the stan
implementation.
report_cases(
case_estimates,
case_forecast = NULL,
delays,
type = "sample",
reporting_effect,
CrIs = c(0.2, 0.5, 0.9)
)
case_estimates |
A data.table of case estimates with the following variables: date, sample, cases |
case_forecast |
A data.table of case forecasts with the following variables: date, sample, cases. If not supplied the default is not to incorporate forecasts. |
delays |
A call to |
type |
Character string indicating the method to use to transform counts. Supports either "sample" which approximates sampling or "median" would shift by the median of the distribution. |
reporting_effect |
A |
CrIs |
Numeric vector of credible intervals to calculate. |
A list of data.table
s. The first entry contains the following
variables sample
, date
and cases
with the second being summarised
across samples.
# This function is deprecated and its functionality can now be accessed
# from [simulate_secondary()].
# Here are some examples of how to use [simulate_secondary()] to replace
# report_cases().
# Old (using report_cases()):
# Define case data
cases <- example_confirmed[1:40]
cases <- cases[, cases := as.integer(confirm)]
cases <- cases[, confirm := NULL][, sample := 1]
reported_cases <- report_cases(
case_estimates = cases,
delays = delay_opts(example_incubation_period + example_reporting_delay),
type = "sample"
)
print(reported_cases$samples)
# New (using simulate_secondary()):
cases <- example_confirmed[1:40]
cases <- cases[, primary := as.integer(confirm)]
report <- simulate_secondary(
cases,
delays = delay_opts(
fix_dist(example_incubation_period + example_reporting_delay)
),
obs = obs_opts(family = "poisson")
)
print(report)
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