draw_epsilon: Draw epsilon from marginal posterior distribution

In annecori/EpiEstim: Estimate Time Varying Reproduction Numbers from Epidemic Curves

Draw epsilon from marginal posterior distribution

Description

Draw epsilon from marginal posterior distribution

Usage

draw_epsilon(
  R,
  incid,
  lambda,
  priors,
  shape_epsilon = NULL,
  t_min = 2L,
  t_max = nrow(incid),
  seed = NULL
)

Arguments

R	a matrix with dimensions containing values of the instantaneous reproduction number for each time step (row) and location (column), for the reference pathogen/strain/variant
incid	a multidimensional array containing values of the (local) incidence for each time step (1st dimension), location (2nd dimension) and pathogen/strain/variant (3rd dimension)
lambda	a multidimensional array containing values of the overall infectivity for each time step (1st dimension), location (2nd dimension) and pathogen/strain/variant (3rd dimension). The overall infectivity for a given location and pathogen/strain/variant represents the sum of the incidence for that location and that pathogen/strain/variant at all previous time steps, weighted by the current infectivity of those past incident cases. It can be calculated from the incidence 'incid' and the distribution of the serial interval using function 'compute_lambda')
priors	a list of prior parameters (shape and scale of a gamma distribution) for epsilon and R; can be obtained from the function 'default_priors'. The prior for R is assumed to be the same for all time steps and all locations
shape_epsilon	a value or vector of values of the shape of the posterior distribution of epsilon for each of the non reference variants, as returned by function 'get_shape_epsilon'
t_min	an integer >1 giving the minimum time step to consider in the estimation. Default value is 2 (as the estimation is conditional on observations at time step 1 and can therefore only start at time step 2).
t_max	an integer >'t_min' and <='nrow(incid)' giving the maximum time step to consider in the estimation. Default value is 'nrow(incid)'.
seed	a numeric value used to fix the random seed

Value

a value or vector of values for epsilon for each non reference pathogen/strain/variant, drawn from the marginal posterior distribution

Examples

n_loc <- 4 # 4 locations
n_v <- 3 # 3 strains
T <- 100 # 100 time steps
priors <- default_priors()
# constant incidence 10 per day everywhere
incid <- array(10, dim = c(T, n_loc, n_v))
incid <- process_I_multivariant(incid)
# arbitrary serial interval, same for both variants
w_v <- c(0, 0.2, 0.5, 0.3)
si_distr <- cbind(w_v, w_v, w_v)
lambda <- compute_lambda(incid, si_distr)
# Constant reproduction number of 1
R <- matrix(1, nrow = T, ncol = n_loc)
R[1, ] <- NA # no estimates of R on first time step
draw_epsilon(R, incid$local, lambda, priors, seed = 1)

annecori/EpiEstim documentation built on Oct. 14, 2023, 1:54 a.m.