sim.cs.multi: Simulate multiple data sets
In serocalculator: Estimating Infection Rates from Serological Data

sim.cs.multi

R Documentation

Simulate multiple data sets

Description

Simulate multiple data sets

Usage

sim.cs.multi(
  nclus = 10,
  lambdas = c(0.05, 0.1, 0.15, 0.2, 0.3),
  num_cores = max(1, parallel::detectCores() - 1),
  rng_seed = 1234,
  renew.params = TRUE,
  add.noise = TRUE,
  verbose = FALSE,
  ...
)

Arguments

`nclus`	number of clusters
`lambdas`	#incidence rate, in events/person*year
`num_cores`	number of cores to use for parallel computations
`rng_seed`	starting seed for random number generator, passed to `rngtools::RNGseq()`
`renew.params`	whether to generate a new parameter set for each infection `renew.params = TRUE` generates a new parameter set for each infection `renew.params = FALSE` keeps the one selected at birth, but updates baseline y0
`add.noise`	a `logical()` indicating whether to add biological and measurement noise
`verbose`	whether to report verbose information
`...`	Arguments passed on to `sim.cs` `lambda` a `numeric()` scalar indicating the incidence rate (in events per person-years) `n.smpl` number of samples to simulate `age.rng` age range of sampled individuals, in years `age.fx` specify the curve parameters to use by age (does nothing at present?) `antigen_isos` Character vector with one or more antibody names. Values must match `curve_params`. `n.mc` how many MCMC samples to use: when `n.mc` is in `1:4000` a fixed posterior sample is used when `n.mc` = `0`, a random sample is chosen `noise_limits` biologic noise distribution parameters `format` a `character()` variable, containing either: `"long"` (one measurement per row) or `"wide"` (one serum sample per row) `curve_params` a `data.frame()` containing MCMC samples of parameters from the Bayesian posterior distribution of a longitudinal decay curve model. The parameter columns must be named: `antigen_iso`: a `character()` vector indicating antigen-isotype combinations `iter`: an `integer()` vector indicating MCMC sampling iterations `y0`: baseline antibody level at $t=0$ ($y(t=0)$) `y1`: antibody peak level (ELISA units) `t1`: duration of infection `alpha`: antibody decay rate (1/days for the current longitudinal parameter sets) `r`: shape factor of antibody decay