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Simulate Data for Inference

Source: R/model_simulation.R
data_sim_for_inference.Rd

This function generates a simulated dataset for inference based on a specified model and parameter values. It supports options for monthly aggregation, adjusting for unequal days in months, and adding stochastic noise to the incidence data.

Usage

data_sim_for_inference(
  model,
  param_inputs,
  dates,
  noise = FALSE,
  month = FALSE,
  month_unequal_days = FALSE
)

Arguments

model

A compiled model object compatible with data_sim(). Typically created using odin.dust::odin_dust().

param_inputs

A named list of parameter values required by the model.

dates

A character vector of length two specifying the start and end dates (e.g., c("2022-01-01", "2022-12-31")).

noise

Logical. If TRUE, random noise is added using a negative binomial distribution. Defaults to FALSE.

month

Logical. If TRUE, the output is aggregated by month. Defaults to FALSE.

month_unequal_days

Logical. If TRUE, accounts for unequal month lengths when aggregating. Defaults to FALSE.

Value

A data frame of simulated incidence data, in the same format as the output of data_sim(). If noise = TRUE, the inc column will include added random variation.

Details

  • When month = TRUE, output is aggregated by month. If month_unequal_days = TRUE, aggregation is adjusted to reflect actual month lengths.

  • If noise = TRUE, the function adds variability to the incidence estimates using a negative binomial distribution with size = 100.

See also

data_sim for the underlying simulation function.

Examples

# Example (requires a model created using odin.dust, not run here):
if (FALSE) { # \dontrun{
model <- odin.dust::odin_dust("path/to/model.R")
param_inputs <- list(beta = 0.3, gamma = 0.1)
dates <- c("2022-01-01", "2022-12-31")

# Simulate data without noise
sim_data <- data_sim_for_inference(model, param_inputs, dates, noise = FALSE)

# Simulate data with noise and monthly aggregation
sim_data_monthly <- data_sim_for_inference(model, param_inputs, dates,
                                           noise = TRUE, month = TRUE)
} # }