fit_hhh4u_homog: Fitting time-homogeneous underreported endemic-epidemic model...

In jbracher/hhh4underreporting: Fitting endemic-epidemic models to underreported data

Description

Fits a time-homogeneous endemic-epidemic model with underreporting using an approximative maximum likelihood scheme. The likelihood approximation is based on an approximation of the process by a second-order equivalent process with complete reporting. The reporting probability cannot be estimated from the data (in most cases these contain no information on it) and thus needs to be specified in advance.

Usage

fit_hhh4u_homog(
  observed,
  q,
  include_kappa = TRUE,
  initial = c(log_nu = 2, log_phi = -1, log_kappa = -2, log_psi = -3),
  max_lag = 5,
  iter_optim = 3,
  hessian = TRUE,
  ...
)

Arguments

observed	a time series of counts (numeric vector)
q	the assumed reporting probability
initial	the initial value of the parameter vector passed to optim (note: the function re-runs optimization several times)
max_lag	in evaluation of (conditional) likelihood only lags up to max_lag are taken into account

Value

a named list containing the following elements:

• parameter estimates on the original scale (codepar) and associated standard errors (se), obtained via the delta method

• parameter estimates on the log scale (as used in the optimization; par_log), associated standard errors (se_log) and inverse Fisher information matrix (Sigma_log)

• the return object of the call to optim (opt)

• the data (observed), reporting probability (q) and other settings settings used in the call to fit_hhh4u_homog

jbracher/hhh4underreporting documentation built on July 21, 2020, 2:08 p.m.