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Optimized LSS with modern signature

Source: R/lss_fit_wrappers.R
lss_optimized_fit.Rd

This is a convenience wrapper around lss() that selects one of the optimized implementations.

Usage

lss_optimized_fit(
  Y,
  X,
  Z = NULL,
  Nuisance = NULL,
  engine = c("cpp", "r"),
  block_size = 96,
  prewhiten = NULL
)

Arguments

Y

Numeric matrix (timepoints x voxels).

X

Trial design matrix (timepoints x trials).

Z

Optional experimental regressors.

Nuisance

Optional nuisance regressors to project out.

engine

"cpp" (default) for method="cpp_optimized" or "r" for method="r_optimized".

block_size

Block size used by the C++ optimized path.

prewhiten

Optional prewhitening options list (see prewhiten_options()).

Value

A numeric matrix (trials x voxels) of beta estimates.

Examples

set.seed(1)
Y <- matrix(rnorm(16), 8, 2)
X <- matrix(0, 8, 2)
X[2:3, 1] <- 1
X[5:6, 2] <- 1
lss_optimized_fit(Y, X, engine = "r")
#>            Voxel_1     Voxel_2
#> Trial_1 -0.8746378  0.09179092
#> Trial_2 -0.7941255 -1.92937571