Find Optimal Design — find_power • designpower

Iteratively search for optimal design parameters using adaptive simulation.

Usage

find_power(
  design,
  design_digits,
  opti,
  sim_power,
  extra_args = list(),
  power = 0.9,
  alpha = 0.1,
  filename = "power.duckdb"
)

Arguments

design: List. Initial design parameters.
design_digits: Named numeric. Precision (number of decimal places) for each parameter. The names must match those in design.
opti: Character. Name of parameter to optimize.
sim_power: Function. Simulation function (should accept design and n_sim).
extra_args: List. Optional additional arguments passed to sim_power. Defaults to an empty list.
power: Numeric. Target power (default 0.9).
alpha: Numeric. Significance level (default 0.1).
filename: Character. Path to DuckDB database file.

Value

Numeric vector. The optimized parameter value and confidence range.

Details

Uses DuckDB to store simulations and gradually refines design parameters to achieve target power.

Examples

if (FALSE) { # \dontrun{
find_power(
  design = list(trend = -0.03, n_site = 20, n_year = 12),
  design_digits = c(trend = 4, n_site = 0, n_year = 0),
  opti = "trend",
  sim_power = sim_power,
  extra_args = list()
)
} # }