cvEigenanatomy¶

purpose:

Cross-validation method for eigenanatomy decompositions.

description:

Perform cross-validation on an image set using eigencomponents to predict an outcome variable.

usage:

cvEigenanatomy(demog, images, outcome, ratio=10, mask=NA,

sparseness=0.01, nvecs=50, its=5, cthresh=250, ...)

examples:

# generate simulated outcome

nsubjects <- 100

x1 <- seq(1, 10, length.out=nsubjects) + rnorm(nsubjects, sd=2)

x2 <- seq(25, 15, length.out=nsubjects) + rnorm(nsubjects, sd=2)

outcome <- 3 * x1 + 4 * x2 + rnorm(nsubjects, sd=1)

# generate simulated images with outcome predicted

# by sparse subset of voxels

voxel.1 <- 3 * x1 + rnorm(nsubjects, sd=2)

voxel.2 <- rnorm(nsubjects, sd=2)

voxel.3 <- 2 * x2 + rnorm(nsubjects, sd=2)

voxel.4 <- rnorm(nsubjects, sd=3)

input   <- cbind(voxel.1, voxel.2, voxel.3, voxel.4)

mask    <- as.antsImage(matrix(c(1,1,1,1), nrow=2))

# generate sample demographics that do not explain outcome

age <- runif(nsubjects, 50, 75)

demog <- data.frame(outcome=outcome, age=age)

result <- cvEigenanatomy(demog, input, "outcome", ratio=5, mask,

            sparseness=0.25, nvecs=4)

ANTsR 0.0.0 documentation

cvEigenanatomy

cvEigenanatomy¶