cudaBayesreg (version 0.3-16)

post.shrinkage.minmax: Computes shrinkage of fitted estimates over regressions

Description

post.shrinkage.minmax computes the maximum and minimum fitted estimates, as a function of the mean regression coefficient estimates over all regressions.

Usage

post.shrinkage.minmax(out, X, vreg, plot=T)

Arguments

out

output of MCMC simulation

X

regression matrix used in the simulation

vreg

number of the regression coefficient

plot

{T,F} output plot (default=T)

Value

yrecmin

minimum values of fitted values

yrecmax

maximum values of fitted values

beta

mean of estimated coefficients over all regressions

Details

The plot helps visualizing shrinkage by analyzing the influence of the hyperparameter $nu$ on the dispersion of the fitted maximum and minimum estimates. Different shrinkage plots may be compared for simulations with different $nu$ values.

See Also

cudaMultireg.slice, read.fmrislice

Examples

## Not run: 
# slicedata <- read.fmrislice(fbase="fmri", slice=3, swap=FALSE)
# ymaskdata <- premask(slicedata)
# fsave <- paste(tempdir(),"/simultest1",fileext = ".sav", sep="")
# nu1 <- 3
# out <- cudaMultireg.slice(slicedata, ymaskdata, R=2000, keep=5, nu.e=nu1,
#   fsave=fsave1, zprior=FALSE, rng=1)
# vreg <- 2
# post.shrinkage.minmax(out, slicedata$X, vreg=vreg) 
# ## End(Not run)