beezdemand (version 0.2.0)

run_hurdle_monte_carlo: Run Monte Carlo Simulation Study for Hurdle Demand Model

Description

Runs a Monte Carlo simulation study to assess model performance, including bias, standard error estimates, and confidence interval coverage.

Usage

run_hurdle_monte_carlo(
  n_sim = 100,
  n_subjects = 100,
  true_params = NULL,
  n_random_effects = 2,
  prices = seq(0, 11, by = 0.5),
  stop_at_zero = TRUE,
  verbose = TRUE,
  seed = NULL
)

Value

A list with:

estimates

Data frame of parameter estimates from each simulation

true_params

True parameter values used

summary

Summary statistics including bias, SE ratio, and coverage

n_converged

Number of simulations that converged

n_sim

Total number of simulations attempted

Arguments

n_sim

Number of simulated datasets. Default is 100.

n_subjects

Number of subjects per dataset. Default is 100.

true_params

Named list of true parameter values. If NULL, defaults are used from simulate_hurdle_data.

n_random_effects

Number of random effects (2 or 3). Default is 2.

prices

Numeric vector of prices. Default is seq(0, 11, by = 0.5).

stop_at_zero

Logical; if TRUE in simulation, subjects stop after first zero. Default is TRUE.

verbose

Logical; print progress. Default is TRUE.

seed

Random seed for reproducibility.

See Also

simulate_hurdle_data, fit_demand_hurdle

Examples

# \donttest{
# Run small simulation study (for demonstration)
mc_results <- run_hurdle_monte_carlo(n_sim = 10, n_subjects = 50, seed = 123)

# View summary
print(mc_results$summary)

# Check convergence rate
cat("Convergence rate:", mc_results$n_converged / mc_results$n_sim, "\n")
# }