View source: R/PreEst.2017Lee.R
PreEst.2017Lee | R Documentation |
PreEst.2017Lee
returns a Bayes estimator of the banded precision matrix,
which is defined in subsection 3.3 of Lee and Lee (2017), using the k-BC prior.
The bandwidth is set at the mode of marginal posterior for the bandwidth parameter.
PreEst.2017Lee(
X,
upperK = floor(ncol(X)/2),
logpi = function(k) {
-k^4
}
)
X |
an |
upperK |
upper bound of bandwidth |
logpi |
log of prior distribution for bandwidth |
a named list containing:
a (p\times p)
MAP estimate for precision matrix.
lee_estimating_2017CovTools
## generate data from multivariate normal with Identity precision.
pdim = 5
data = matrix(rnorm(100*pdim), ncol=pdim)
## compare different K
out1 <- PreEst.2017Lee(data, upperK=1)
out2 <- PreEst.2017Lee(data, upperK=3)
out3 <- PreEst.2017Lee(data, upperK=5)
## visualize
opar <- par(no.readonly=TRUE)
par(mfrow=c(2,2), pty="s")
image(diag(pdim)[,pdim:1], main="Original Precision")
image(out1$C[,pdim:1], main="banded2::upperK=1")
image(out2$C[,pdim:1], main="banded2::upperK=3")
image(out3$C[,pdim:1], main="banded2::upperK=5")
par(opar)
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