View source: R/plot.BayesSUR.R
plot.BayesSUR | R Documentation |
plot method for class BayesSUR
. This is the main plot function to be
called by the user. This function calls one or several of the following
functions: plotEstimator()
, plotGraph()
, plotMCMCdiag()
,
plotManhattan()
, plotNetwork()
, plotCPO()
.
## S3 method for class 'BayesSUR'
plot(x, estimator = NULL, type = NULL, ...)
x |
an object of class |
estimator |
It is in
|
type |
It is one of
|
... |
other arguments, see functions |
data("exampleEQTL", package = "BayesSUR")
hyperpar <- list(a_w = 2, b_w = 5)
set.seed(9173)
fit <- BayesSUR(
Y = exampleEQTL[["blockList"]][[1]],
X = exampleEQTL[["blockList"]][[2]],
data = exampleEQTL[["data"]], outFilePath = tempdir(),
nIter = 2, burnin = 0, nChains = 1, gammaPrior = "hotspot",
hyperpar = hyperpar, tmpFolder = "tmp/"
)
## check output
## Not run:
## Show the interactive plots. Note that it needs at least 2000*(nbloc+1) iterations
## for the diagnostic plots where nbloc=3 by default
# plot(fit)
## End(Not run)
## plot heatmaps of the estimated beta, gamma and Gy
plot(fit, estimator = c("beta", "gamma", "Gy"), type = "heatmap")
## plot estimated graph of responses Gy
plot(fit, estimator = "Gy", type = "graph")
## plot network between response variables and associated predictors
plot(fit, estimator = c("gamma", "Gy"), type = "network")
## print Manhattan-like plots
plot(fit, estimator = "gamma", type = "Manhattan")
## print MCMC diagnostic plots
#plot(fit, estimator = "logP", type = "diagnostics")
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.