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cudaBayesreg (version 0.2-1)

post.ppm: Posterior Probability Map (PPM) Image

Description

post.ppm depicts the PPM image of voxel activations in a slice.

Usage

post.ppm(out, slicedata, vreg = 2, swap = F, plot=T)

Arguments

Value

a list containingppmppm image as matrixnactiven. of active voxels

concept

PPM Image

Details

Use the MCMC draws to estimate the Posterior Probability Map (PPM) Image. The number of regression variables used in the simulation is equal to the number of columns specified in the design matrix, plus an intercept term; vreg=1 represents the intercept term in regression.

References

Adelino R. Ferreira da Silva "A Bayesian Multilevel Model for fMRI Data Analysis", to be published.

See Also

cudaMultireg.slice regpostsim post.simul.hist post.tseries

Examples

Run this code
slicedata <- read.fmrisample(slice=3)
fsave <- "/tmp/simultest.sav"
answ <- readline("Run MCMC simulation first ? ")
run <- FALSE
if (substr(answ, 1, 1) == "y") { run <- TRUE }
if(run) {
	out <- cudaMultireg.slice(slicedata, fsave=fsave )
} else {
	load(file=fsave)
	cat("loaded",fsave,"\n")
}
post.ppm(out=out, slicedata=slicedata, vreg=2)
post.ppm(out=out, slicedata=slicedata, vreg=4)

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