observation_process_single_logp: Calculates observation process log probability density for a...

In ben18785/incidenceinflation: Estimate R0 Given Case Reporting Delays

Calculates observation process log probability density for a pair of days

Description

The probability of observations is a function of the number of cases remaining to be reported:

I_remaining = I_true - I_day_1

and the number of cases observed between day_1 and day_2:

I_obs = I_day_2 - I_day_1

It is given by:

binomial(I_obs|I_remaining, p_detect)

where p_detect is the probability a thus undetected case is detected between day_1 and day_2.

Usage

observation_process_single_logp(
  cases_true,
  cases_day_2,
  cases_day_1,
  day_2,
  day_1,
  day_onset,
  reporting_parameters
)

Arguments

cases_true	true case count(s) originating on day_onset: can be a single value or vector
cases_day_2	number of cases arising on day_onset observed by day_2
cases_day_1	number of cases arising on day_onset observed by day_1 < day_2
day_2	day of last observation: day_2 > day_1 >= day_onset
day_1	day of first observation: day_1 >= day_onset
day_onset	day when case originates
reporting_parameters	named list of 'mean' and 'sd' of gamma distribution characterising the reporting delay distribution

Value

a log-probability or vector of log-probabilities

ben18785/incidenceinflation documentation built on Feb. 8, 2024, 2:36 a.m.