Build an input block for automatic parameter selection

Creates an unevaluated {} expression that calls pick_val_v() with the correct arguments for base case, PSA, DSA, and scenario analyses. The expression is meant to be passed directly to run_sim() or run_sim_parallel() as a *_inputs argument.

Usage

input_block(
  .data = NULL,
  base,
  psa,
  sens,
  names_out,
  psa_indicators = NULL,
  sens_indicators = NULL,
  indicator_sens_binary = FALSE,
  dsa_names = NULL,
  distributions = NULL,
  covariances = NULL
)

Arguments

.data: Optional existing {} block to prepend (for pipe chaining).
base: A list of base case values, one entry per parameter.
psa: An unevaluated expression producing PSA draws (e.g. pick_psa(...)), evaluated at runtime per simulation.
sens: The sensitivity data object (e.g. l_inputs). At runtime the engine indexes it as sens[[sens_name_used]] to pick the active column.
names_out: Character vector or list of strings of output parameter names.
psa_indicators: List of 0/1 indicators controlling which parameters draw from PSA. NULL means all parameters draw from PSA.
sens_indicators: List of indicators, one entry per parameter (may be a scalar or a vector for vector-valued parameters). In binary mode: 0 = inactive, 1 = active. In grouped mode: 0 = inactive, same integer = varied together. NULL means all parameters are active. Only in grouped mode can subparameters (e.g., elements of a vector parameter) be varied at different steps of a DSA.
indicator_sens_binary: Logical. TRUE = binary (0/1) mode; each active parameter is varied independently via create_indicators(). FALSE (default) = grouped integer mode when sens_indicators and distributions are supplied; otherwise falls back to binary mode.
dsa_names: Character vector of sensitivity_names values that are DSA directions (e.g. c("DSA_min","DSA_max")). Those names iterate through active parameters/groups one at a time. All other names passed to sensitivty_names in run_sim() are treated as scenarios. NULL (the default) means all sensitivity names are scenarios.
distributions: List of distribution names (e.g. "rnorm", "mvrnorm", "rdirichlet"), required in grouped mode to determine which parameters are vectors and require conditional distributions.
covariances: List of covariance matrices or scalars, required for "mvrnorm" / "rdirichlet" distributions.

Value

A {} language object (same type as add_item()) with a warden_block_meta attribute used by the engine to build the iteration schedule.

Details

Supports two modes:

Binary (indicator_sens_binary = TRUE): sens_indicators are 0/1 per parameter. Each non-zero parameter is varied independently via create_indicators().
Grouped (indicator_sens_binary = FALSE, the default when sens_indicators and distributions are supplied): sens_indicators are integer group labels. Parameters sharing the same integer are varied together; 0 means the parameter is never varied.

DSA vs scenario analyses

Supply dsa_names with the subset of sensitivity_names that correspond to DSA directions (e.g. c("DSA_min","DSA_max")). Each DSA name runs one iteration per active parameter/group; other names (scenarios) apply all active parameters simultaneously in a single iteration.

When dsa_names = NULL (the default) every sensitivity name is treated as a scenario — all active parameters take their scenario value at once, one iteration per sensitivity_names entry. This is the correct default when there is no DSA.

`sens_indicators` and zeros

Any parameter whose sens_indicators entry is 0 (or all-zero for vector-valued parameters) is never varied: it always uses the base or PSA value regardless of whether we are running a DSA or a scenario. This applies to both modes.

Examples

l_inputs <- list(
  parameter_name = list("util.sick", "util.sicker"),
  base_value     = list(0.8, 0.5),
  PSA_dist       = list("rnorm", "rbeta_mse"),
  a              = list(0.8, 0.5),
  b              = list(0.04, 0.025),
  n              = list(1, 1),
  DSA_min        = list(0.6, 0.3),
  DSA_max        = list(0.9, 0.7),
  psa_indicators = list(1, 1)
)

blk <- input_block(
  base                  = l_inputs[["base_value"]],
  psa                   = pick_psa(l_inputs[["PSA_dist"]], l_inputs[["n"]],
                                   l_inputs[["a"]], l_inputs[["b"]]),
  sens                  = l_inputs,
  names_out             = l_inputs[["parameter_name"]],
  psa_indicators        = l_inputs[["psa_indicators"]],
  indicator_sens_binary = TRUE,
  dsa_names             = c("DSA_min", "DSA_max")
)
stopifnot(is.call(blk))
stopifnot(!is.null(attr(blk, "warden_block_meta")))