Runs the epidemiological model multiple times using different parameter sets sampled from MCMC results. Each simulation is optionally prewarmed using a specified number of years prior to the start date.
Usage
simulate_models(
model,
param_inputs,
sampled_params,
start_date,
end_date,
prewarm_years = 2,
days_per_year = 360
)Arguments
- model
The model function to simulate from.
- param_inputs
A list of baseline parameters to be updated with each sampled parameter set.
- sampled_params
A list of named parameter sets, typically obtained from posterior samples.
- start_date
Character string giving the start date for the simulation (e.g., "2021-01-01").
- end_date
Character string giving the end date for the simulation (e.g., "2021-12-31").
- prewarm_years
Integer specifying how many years before
start_dateto simulate for model prewarming (default is 2).- days_per_year
Integer specifying the number of days per simulation year (default is 360).
Value
A list of data frames. Each data frame contains the simulation results for a different parameter set.
Examples
if (FALSE) { # \dontrun{
# Example setup with a dummy model and parameters
model <- your_model_function # Replace with your actual model function
param_inputs <- return_default_inputs() # Replace with your actual input generator
# Simulate posterior parameter samples
posterior_samples <- matrix(rnorm(30), nrow = 10, ncol = 3)
colnames(posterior_samples) <- c("alpha", "beta", "gamma")
# Convert to list of named parameter sets
sampled_params <- lapply(1:nrow(posterior_samples), function(i) {
as.list(posterior_samples[i, ])
})
# Run simulations
simulations <- simulate_models(
model = model,
param_inputs = param_inputs,
sampled_params = sampled_params,
start_date = "2021-01-01",
end_date = "2021-12-31"
)
} # }