simulate_individual: Simulate individual data

In seroanalytics/serosolver: Inference Framework for Serological Data

Simulate individual data

Description

Simulates a full set of titre data for an individual with known theta and infection_history.

Usage

simulate_individual(
  theta,
  infection_history,
  antigenic_map,
  sampling_times,
  strain_isolation_times,
  measured_strains,
  mus = NULL,
  mu_indices = NULL,
  measurement_bias = NULL,
  measurement_indices = NULL,
  add_noise = TRUE,
  repeats = 1,
  DOB = NULL
)

Arguments

theta	the named parameter vector
infection_history	the vector of 1s and 0s giving presence/absence of infections
antigenic_map	(optional) A data frame of antigenic x and y coordinates. Must have column names: x_coord; y_coord; inf_times. See example_antigenic_map
sampling_times	vector of times at which blood samples were taken
strain_isolation_times	(optional) If no antigenic map is specified, this argument gives the vector of times at which individuals can be infected
measured_strains	vector of which strains had titres measured in 'strain_isolation_times'
mus	default NULL, optional vector of boosting parameters for each strain
mu_indices	default NULL, optional vector giving the index of 'mus' that each strain uses the boosting parameter from. eg. if there are 6 circulation years in strain_isolation_times and 3 strain clusters, then this might be c(1,1,2,2,3,3)
measurement_indices	default NULL, optional vector giving the index of ‘measurement_bias' that each strain uses the measurement shift from from. eg. if there’s 6 circulation years and 3 strain clusters, then this might be c(1,1,2,2,3,3)
add_noise	if TRUE, adds observation noise to the simulated titres
repeats	number of repeat observations for each year

Value

a data frame with columns samples, virus and titre of simulated data

See Also

Other simulation_functions: simulate_attack_rates(), simulate_data(), simulate_group(), simulate_individual_faster(), simulate_infection_histories()

Examples

data(example_par_tab)
data(example_antigenic_map)
infection_history <- sample(c(0,1),size=nrow(example_antigenic_map), replace=TRUE,prob=c(0.9,0.1))
pars <- example_par_tab$values
names(pars) <- example_par_tab$names
strain_isolation_times <- example_antigenic_map$inf_times
y <- simulate_individual(pars, infection_history, example_antigenic_map, 2009, 
                         strain_isolation_times,strain_isolation_times,add_noise=FALSE)

seroanalytics/serosolver documentation built on April 24, 2023, 9:52 a.m.