Learn R Programming

vows (version 0.5)

Voxelwise Semiparametrics

Description

Parametric and semiparametric inference for massively parallel models, i.e., a large number of models with common design matrix, as often occurs with brain imaging data.

Copy Link

Version

Install

install.packages('vows')

Monthly Downloads

70

Version

0.5

License

GPL (>= 2)

Maintainer

Philip Reiss

Last Published

August 21st, 2016

Functions in vows (0.5)

plot.semipar.mp

Plot massively parallel semiparametric models
plot.rlrt4d

Display cross-sections of voxelwise RLRT results
lm4d

Voxelwise linear models
funkmeans

Functional k-means clustering for parallel smooths
plot.funkmeans

Plotting of k-means clustering results for massively parallel smooths
Fdr.rlrt

False discovery rate estimation for massively parallel restricted likelihood ratio tests
funkmeans4d

Functional k-means clustering for parallel smooths for 4-dimensional data
extract.fd

Extract curve estimates to be clustered
nii2R

NIfTI-to-R conversion
qplsc.mp

Quadratically penalized least squares with constraints
screen.vox

Screen voxels for a voxelwise smoothing object
R2nii

Save data to a NIfTI file
vows-mgcv

Utility functions related to the mgcv package
semipar4d

Massively parallel semiparametric regression for 4-dimensional data
rlrt.mp.fit

Massively parallel restricted likelihood ratio tests (internal)
rlrt4d

Voxelwise restricted likelihood ratio tests
rlrt.mp

Massively parallel restricted likelihood ratio tests
vows-internal

Internal functions for the vows package
semipar.mp

Massively parallel semiparametric regression
sf

Defining smooth functions in semiparametric model formulae
vows-package

Voxelwise semiparametrics