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vows (version 0.2-0)

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.

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Version

Install

install.packages('vows')

Monthly Downloads

11

Version

0.2-0

License

GPL (>= 2)

Maintainer

Lan Huo

Last Published

September 7th, 2012

Functions in vows (0.2-0)

Screen voxels for a voxelwise smoothing object

Voxelwise restricted likelihood ratio tests

Save data to a NIfTI file

Massively parallel restricted likelihood ratio tests

Internal functions for the vows package

Functional k-means clustering for parallel smooths for 4-dimensional data

False discovery rate estimation for massively parallel restricted likelihood ratio tests

Voxelwise semiparametrics

Permutation F-tests for massively parallel linear models

Massively parallel semiparametric regression for 4-dimensional data

Massively parallel semiparametric mixed models

Massively parallel linear regression models

Quadratically penalized least squares with constraints

plot.semipar.mp

Plot massively parallel semiparametric models

Interactive visualization of voxelwise RLRT results

Display cross-sections of voxelwise RLRT results

Functional k-means clustering for parallel smooths

Utility functions related to the mgcv package

Plotting of k-means clustering results for massively parallel smooths

Massively parallel restricted likelihood ratio tests (internal)

Defining smooth functions in semiparametric model formulae

Massively parallel semiparametric regression

Summarizing massively parallel linear model fits

F-tests for massively parallel linear models

Voxelwise linear models

NIfTI-to-R conversion

Interactive visualization of massively parallel smoothing results