compute_sop_tv: Marginal second-order properties of an underreported model

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

Description

Compute the time-varying mean and covariance structure of an underreported model.

Usage

compute_sop_tv(lambda1, nu, phi, kappa, psi, q, compute_Sigma = FALSE)

Arguments

lambda1	the initial value of lambda
nu, phi, kappa, psi	the time-varying parameters of the model (kappa and psi are also allowed to be time-varying here); vectors of equal length
q	the reporting probability
compute_Sigma	logical: shall a full covariance matrix be computed?

Value

a named list containing the means, variances, first-order autocovariances. decay parameters of the autocovariance functions and, if desired, full autocovariance matrix for both X and \tilde{X}.

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