MixfMRI (version 0.1-3)

Simulations: Generate datasets for MixfMRI simulations

Description

Generate datasets for MixfMRI simulations

Usage

gendataset(phantom, overlap, smooth = FALSE)

Value

Return a list contains eta for mixing proportion,

overlap for the desired level, mu for center of p-values,

class.id for the true classifications where p-values belong to,

tval for the testing statistics, and pval for the p-values of interesting in simulations.

Arguments

phantom

a phantom dataset.

overlap

a desired overlap level.

smooth

if gcv.smooth2d() be applied to the data.

Author

Wei-Chen Chen and Ranjan Maitra.

Details

This is a function to generate simulated fMRI data based on the input phantom and the desired overlap level for the fMRI p-value.

References

Chen, W.-C. and Maitra, R. (2021) “A Practical Model-based Segmentation Approach for Accurate Activation Detection in Single-Subject functional Magnetic Resonance Imaging Studies”, arXiv:2102.03639.

See Also

set.global().

Examples

# \donttest{
.rem <- function(){

  library(MixfMRI, quietly = TRUE)
  set.seed(1234)
  da <- gendataset(phantom = shepp1fMRI, overlap = 0.01)$pval
  da2 <- gendataset(phantom = shepp2fMRI, overlap = 0.01)$pval

  par(mfrow = c(2, 2), mar = rep(0.05, 4))
  image(shepp1fMRI[50:210, 50:210], axes = FALSE)
  image(shepp2fMRI[50:210, 50:210], axes = FALSE)
  image(da[50:210, 50:210], axes = FALSE)
  image(da2[50:210, 50:210], axes = FALSE)

}
# }