Fit OASIS with HRF Grid Search

Selects an LWU HRF by joint-model profile fit, then estimates OASIS betas.

Usage

fit_oasis_grid(Y, onsets, sframe, hrf_grid, ridge_x = 0.01, ridge_b = 0.01)

Arguments

Y

Data matrix (time x voxels)

onsets

Event onset times

sframe

Sampling frame

hrf_grid

List of HRF models to test

ridge_x

Ridge parameter for design matrix

ridge_b

Ridge parameter for aggregator

Value

List with best HRF index, parameters, and beta estimates

Details

Each candidate is scored by pooled R-squared from unpenalized joint least squares with a voxel-specific intercept and all trial columns. The denominator sums squared deviations from each voxel's own mean. Ridge parameters affect only the final LSS estimates, not HRF selection. Simulation, scoring, and fitting use the same event construction at 0.1-second precision. This is an in-sample selection criterion; overlapping events can leave HRF parameters weakly identifiable.

Examples

# \donttest{
onsets <- generate_rapid_design(n_events = 4, total_time = 60, seed = 1)
sim <- generate_lwu_data(onsets, total_time = 60, n_voxels = 2, seed = 1)
grid <- create_lwu_grid(n_tau = 2, n_sigma = 2, n_rho = 2)
fit <- fit_oasis_grid(sim$Y, sim$onsets, sim$sframe, grid)
fit$best_params
#>   tau sigma rho
#> 4   8   3.5 0.1
# }