sccanBasedDecoder: Simple eigenSentence estimation function.

In stnava/RKRNS: ANTsR Decoding

Description

Applies a function to a matrix representation of a sentence to get an eigensentence map.

Usage

sccanBasedDecoder(eventdata, designmat, boldFeatureMatrix, sentenceSpace,
  mysparse = c(-0.1, -0.1), nvecs = 5, its = 1, smooth = 0,
  cthresh = 0, mask = NA, strategy = NA, doEanat = F, joinEanat = F,
  outputfileprefix = "sccanBasedDecoder", interleave = FALSE,
  sentenceTransformation = "none", trainset = NA, locwordlist = "")

Arguments

eventdata	output from annotateEvents
designmat	sentences part of the assembled design matrix
boldFeatureMatrix	a feature matrix for bold data, currently spatiotemporal
sentenceSpace	the sentence feature space
mask	a 4D mask
doEanat	also run a sparse PCA on the data
otherparameters	see sparseDecom2 documentation

Value

a data frame with annotation and ground truth vs prediction annotated ...

Author(s)

Avants BB

Examples

## Not run: 
 ccaresults<-sccanBasedDecoder( eventdata, dmats, ccafeatspace , sentspace )

## End(Not run)

stnava/RKRNS documentation built on May 30, 2019, 7:21 p.m.