Description Usage Arguments Details Value Author(s) References See Also
Summarizing, printing, and plotting the contents of a
"blasso"
class object containing samples from
the posterior distribution of a Bayesian lasso model
1 2 3 4 5 6 7 8 9 10  ## S3 method for class 'blasso'
print(x, ...)
## S3 method for class 'blasso'
summary(object, burnin = 0, ...)
## S3 method for class 'blasso'
plot(x, which=c("coef", "s2", "lambda2", "gamma",
"tau2i","omega2", "nu", "m", "pi"), subset = NULL, burnin = 0,
... )
## S3 method for class 'summary.blasso'
print(x, ...)

object 
a 
x 
a 
subset 
a vector of indicies that can be used to specify
the a subset of the columns of 
burnin 
number of burnin rounds to discard before
reporting summaries and making plots. Must be nonnegative
and less than 
which 
indicates the parameter whose characteristics
should be plotted; does not apply to the 
... 
passed to 
print.blasso
prints the call
followed by a
brief summary of the MCMC run and a suggestion to try
the summary and plot commands.
plot.blasso
uses an appropriate
plot
command on the list
entries of the
"blasso"
class object thus
visually summarizing the samples from the posterior distribution of
each parameter in the model depending on the which
argument supplied.
summary.blasso
uses the summary
command
on the list entries of the "blasso"
class object thus
summarizing the samples from the posterior distribution of each
parameter in the model.
print.summary.monomvn
calls print.blasso
on the object
and then prints the result of
summary.blasso
summary.blasso
returns a "summary.blasso"
class
object, which is a list
containing (a subset of) the items below.
The other functions do not return values.
B 
a copy of the input argument 
T 
total number of MCMC samples to be collected from 
thin 
number of MCMC samples to skip before a sample is
collected (via thinning) from 
coef 
a joint 
s2 
a 
lambda2 
a 
lambda2 
a 
tau2i 
a 
omega2 
a 
nu 
a 
bn0 
the estimated posterior probability that the individual
components of the regression coefficients 
m 
a 
pi 
the estimated Binomial proportion in the prior for
the model order when 2vector input is provided for

Robert B. Gramacy rbg@vt.edu
http://bobby.gramacy.com/r_packages/monomvn
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