mcstatsim (version 0.5.0)

runsim: Run Monte Carlo Simulations in Parallel

Description

This function executes a series of Monte Carlo simulations in parallel, providing detailed progress updates.

Usage

runsim(
  n,
  grid_params,
  sim_func,
  show_progress = TRUE,
  num_cores = parallel::detectCores() - 1
)

Value

A combined dataframe of all simulation results.

Arguments

n

The number of times the simulation function should be executed for each set of parameters. Must be a positive integer.

grid_params

A dataframe where each row corresponds to a unique combination of parameters for the simulation. Typically generated using `expand.grid`.

sim_func

The simulation function to be applied. This function should accept parameters corresponding to a row in `grid_params` and return a dataframe or a list that can be row-bound.

show_progress

Logical indicating whether to display progress messages during the execution of the simulations.

num_cores

The number of cores to use for parallel execution. The default is one less than the total number of cores available on the system.

Details

The function first validates the input parameters. It then uses parallel processing to apply `sim_func` to each combination of parameters specified in `grid_params`, repeating each simulation `n` times. The results are combined into a single dataframe.

Examples

if (FALSE) {
library(mcstatsim)

# Define a simple simulation function
sim_function <- function(a, b) {
  Sys.sleep(0.1)  # Simulate a time-consuming process
  return(data.frame(result = a + b))
}

# Generate a grid of parameters
params <- expand.grid(a = 1:3, b = 4:6)

# Run simulations
results <- runsim(n = 1, grid_params = params, sim_func = sim_function)
print(results)
}