plot.MCMCdiag

0th

Percentile

show trace plots and diagnostic density plots

Show trace plots and diagnostic density plots of a fitted model object of class "BayesSUR".

Usage
# S3 method for MCMCdiag
plot(x, nbloc = 3, HIWg = NULL, header = "", ...)
Arguments
x

an object of class getEstimator with estimator="logP"

nbloc

number of splits for the last half iterations after substracting burn-in length

HIWg

diagnostic plot of the response graph. Default is NULL. HIW="degree" prints the diagnostic of the degrees of response nodes. HIW="edges" prints the diagnostic of every edge between two responses. HIW="lik" prints the diagnostic of the posterior likelihoods of the hyperparameters related to the response relationships

header

the main title

...

other arguments for the plots of the log-likelihood and model size

Aliases
  • plot.MCMCdiag
Examples
# NOT RUN {
data("example_eQTL", package = "BayesSUR")
hyperpar <- list( a_w = 2 , b_w = 5 )

set.seed(9173)
fit <- BayesSUR(Y = example_eQTL[["blockList"]][[1]], 
                X = example_eQTL[["blockList"]][[2]],
                data = example_eQTL[["data"]], outFilePath = tempdir(),
                nIter = 100, burnin = 50, nChains = 2, gammaPrior = "hotspot",
                hyperpar = hyperpar, tmpFolder = "tmp/" )

## check output
MCMCdiag <- getEstimator(fit, estimator = "logP")
plot(MCMCdiag)

# }
Documentation reproduced from package BayesSUR, version 1.1-2, License: MIT + file LICENSE

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