Expand a named parameter vector into the matrix used by simulate() and
log_likelihood(). Each trial receives the same parameter values; rows are
grouped by trial, with accumulators in their model declaration order.
Arguments
- model
Finalized model structure.
- param_values
Named numeric vector using the names from
par_names(). Omitted nondecision-time parameters (t0) default to zero. Supply all other parameters on their natural scale, after any fitting transformations.- n_trials
Positive integer number of trial blocks to create.
Value
A numeric matrix with one row per trial/accumulator pair. Columns
contain trigger absence probability q, nondecision time t0, distribution
parameters p1, p2, and so on, followed by sampled mixture weights.
Distribution slots follow the order listed in the Supported Distributions
vignette. Accumulators without a trigger have q = 0.
Details
Parameter domains are checked before expansion. All values must be
finite, t0 must be nonnegative, and distribution scales must be positive.
Trigger probabilities must lie in [0, 1]; sampled mixture weights must be
nonnegative and sum to at most one. See
vignette("distributions", package = "AccumulatR") for distribution-specific
constraints.
For trial-specific parameters, modify the relevant matrix rows while preserving their order and column layout. Likelihood and simulation calls use those values directly, so modified values must satisfy the same domains.
Examples
spec <- race_spec()
spec <- add_accumulator(spec, "A", "lognormal")
spec <- add_outcome(spec, "A_win", "A")
vals <- c(m = 0, s = 0.1)
build_param_matrix(finalize_model(spec), vals, n_trials = 2)
#> q t0 p1 p2
#> [1,] 0 0 0 0.1
#> [2,] 0 0 0 0.1
#> attr(,"class")
#> [1] "accumulatr_parameters" "matrix" "array"