fit_hhh4u_seasonal: Fits a sesaonal endemic-epidemic model with underreporting...

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

Description

Fits a sesaonal 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_seasonal(
  observed,
  L,
  q,
  seas_phi = FALSE,
  include_kappa = TRUE,
  initial = c(alpha_nu = 4, gamma_nu = 0, delta_nu = 0, alpha_phi = -1, gamma_phi = 0,
    delta_phi = 0, alpha_kappa = -1, log_psi = -3),
  max_lag = 10,
  iter_optim = 3,
  ...
)

Arguments

observed	a time series of counts (numeric vector)
L	the number of observations per period (integer; e.g. 52 for weekly data and yearly seasonality)
q	the assumed reporting probability
seas_phi	should seasonality also be accounted for in the autoregressive parameter $phi$? or only in the immigration parameter $nu$?
include_kappa	should the parameter $kappa$ and thus lagged versions of the conditional expectation $lambda$ be included?
initial	the initial value of the parameter vector passed to optim (note: the function tries different starting values in any case)
max_lag	in evaluation of likelihood only lags up to max_lag are taken into account

Value

the return object from optim providing the maximum likelihood estimates (mostly on the log scale).

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