Creates, manipulates, and evaluates hemodynamic response functions
    and event-related regressors for functional magnetic resonance imaging data
    analysis. Supports multiple basis sets including Canonical, Gamma, Gaussian,
    B-spline, and Fourier bases. Features decorators for time-shifting and blocking,
    and efficient convolution algorithms for regressor construction. Methods are based
    on standard fMRI analysis techniques as described in Jezzard et al. (2001, ISBN:9780192630711).

Methods for performing fMRI quality assurance (QA) measurements of
  test objects. Heavily  based on the fBIRN procedures detailed by Friedman and 
  Glover (2006) <doi:10.1002/jmri.20583>.

Data-driven fMRI denoising with projection scrubbing (Pham et al 
    (2022) <doi:10.1016/j.neuroimage.2023.119972>). Also includes routines for 
    DVARS (Derivatives VARianceS) (Afyouni and Nichols (2018) 
    <doi:10.1016/j.neuroimage.2017.12.098>), motion scrubbing (Power et al 
    (2012) <doi:10.1016/j.neuroimage.2011.10.018>), aCompCor (anatomical 
    Components Correction) (Muschelli et al (2014)
    <doi:10.1016/j.neuroimage.2014.03.028>), detrending, and nuisance
    regression. Projection scrubbing is also applicable to other
    outlier detection tasks involving high-dimensional data.

Supports fMRI (functional magnetic resonance imaging) 
    analysis tasks including reading in 'CIFTI', 'GIFTI' and 
    'NIFTI' data, temporal filtering, nuisance regression, and 
    aCompCor (anatomical Components Correction) (Muschelli et al.
    (2014) <doi:10.1016/j.neuroimage.2014.03.028>).

Several utility functions for the book entitled 
	"Practices of Medical and Health Data Analysis using R"
	(Pearson Education Japan, 2007) with Japanese demographic
	data and some demographic analysis related functions.

Fit linear regression models where the random errors follow a finite mixture of of Skew Heavy-Tailed Errors.

Some basic procedures for dealing
        with log maximally skew stable distributions, which are also
        called finite moment log stable distributions.