simulate antibody kinetics of y over a time interval

Usage

simresp.tinf(
  lambda,
  t_end,
  age_fixed,
  antigen_isos,
  n_mcmc_samples = 0,
  renew_params,
  predpar,
  ...
)

Arguments

lambda

seroconversion rate (1/days),

t_end

end of time interval (beginning is time 0) in days(?)

age_fixed

parameter estimates for fixed age (age_fixed in years) or not. when age_fixed = NA then age at infection is used.

antigen_isos

antigen isotypes

n_mcmc_samples

a posterior sample may be selected (1:4000), or not when n_mcmc_samples = 0 a posterior sample is chosen at random.

renew_params

At infection, a new parameter sample may be generated (when renew_params = TRUE). Otherwise (when renew_params = FALSE), a sample is generated at birth and kept, but baseline y0 are carried over from prior infections.

predpar

an array() with dimensions named:

antigen_iso
parameter
obs

...

Arguments passed on to ldpar, ab, mk_baseline

age

age at infection

nmc

mcmc sample to use

npar

number of parameters

t

numeric vector of elapsed times since start of infection

par

numeric matrix of model parameters:

rows are parameters
columns are biomarkers

kab

integer indicating which row to read from blims

n

number of observations

blims

range of possible baseline antibody levels

Value

a list with:

t = times (in days, birth at day 0),
b = bacteria level, for each antibody signal (not used; probably meaningless),
y = antibody level, for each antibody signal
smp = whether an infection involves a big jump or a small jump
t.inf = times when infections have occurred.