Equivalent to calling lss(..., method = "naive").
Usage
lss_naive_fit(Y, X, Z = NULL, Nuisance = NULL, 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.
- 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_naive_fit(Y, X)
#> Voxel_1 Voxel_2
#> Trial_1 -0.8746378 0.09179092
#> Trial_2 -0.7941255 -1.92937571