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vows (version 0.4)

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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Install

install.packages('vows')

Monthly Downloads

11

Version

0.4

License

GPL (>= 2)

Maintainer

Philip Reiss

Last Published

February 12th, 2015

Functions in vows (0.4)

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

Summarizing massively parallel linear model fits

Interactive visualization of massively parallel smoothing results

Massively parallel semiparametric regression

Quadratically penalized least squares with constraints

Utility functions related to the mgcv package

Permutation F-tests for massively parallel linear models

Massively parallel restricted likelihood ratio tests

Voxelwise restricted likelihood ratio tests

Internal functions for the vows package

Defining smooth functions in semiparametric model formulae

Plotting of k-means clustering results for massively parallel smooths

Massively parallel semiparametric regression for 4-dimensional data

F-tests for massively parallel linear models

NIfTI-to-R conversion

Interactive visualization of voxelwise RLRT results

Display cross-sections of voxelwise RLRT results

Massively parallel semiparametric mixed models

Voxelwise linear models

Massively parallel linear regression models

Save data to a NIfTI file

False discovery rate estimation for massively parallel restricted likelihood ratio tests

Voxelwise semiparametrics

Functional k-means clustering for parallel smooths

plot.semipar.mp

Plot massively parallel semiparametric models

Screen voxels for a voxelwise smoothing object

Extract curve estimates to be clustered

Massively parallel restricted likelihood ratio tests (internal)