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collect cross-sectional data

Source: R/simcs.tinf.R
simcs.tinf.Rd

collect cross-sectional data

Usage

simcs.tinf(
  lambda,
  n_samples,
  age_range,
  age_fixed = NA,
  antigen_isos,
  n_mcmc_samples = 0,
  renew_params = FALSE,
  ...
)

Arguments

lambda

seroconversion rate (in events/person-day)

n_samples

number of samples n_samples (= nr of simulated records)

age_range

age range to use for simulating data, in days

age_fixed

age_fixed for parameter sample (age_fixed = NA for age at infection)

antigen_isos

character vector with one or more antibody names. Values must match curve_params.

n_mcmc_samples

  • when n_mcmc_samples is in 1:4000, a fixed posterior sample is used

  • when n_mcmc_samples = 0 a random sample is chosen

renew_params

  • renew_params = TRUE generates a new parameter set for each infection

  • renew_params = FALSE keeps the one selected at birth, but updates baseline y0

...

Arguments passed on to simresp.tinf

predpar

an array() with dimensions named:

  • antigen_iso

  • parameter

  • obs

Value

an array() with dimensions n_samples, length(antigen_isos) + 1, where rows are observations and columns are age and biomarkers y(t)