summary.MCMC {bayeslm}  R Documentation 
Summarize posterior draws
Description
summary.MCMC
is an S3 method to summarize posterior draws of the model. The input should be a matrix of draws.
Usage
## S3 method for class 'MCMC'
summary(object,names,burnin=trunc(.1*nrow(X)),quantiles=FALSE,trailer=TRUE,...)
Arguments
object 

names 
an optional character vector of names for the columns of 
burnin 
number of draws to burnin (default value is 
quantiles 
logical for should quantiles be displayed (def: 
trailer 
logical for should a trailer be displayed (def: 
... 
optional arguments for generic function. 
Details
This function is modified from package bayesm
by Peter Rossi. It summarize object MCMC
. Mean, Std Dev, effective sample size (computed by function effectiveSize
in package coda
) are displayed. If quantiles=TRUE
, quantiles of marginal distirbutions in the columns of X
are displayed.
The function also returns significance level, defined by whether the symmetric posterior quantilebased credible interval excludes zero. For example, a regression coefficient with one * has 0.025 quantile and 0.975 quantile with the same sign. Similarly, '***' denotes 0.0005 and 0.9995, '**' denotes 0.005 and 0.995, '*' denotes 0.025 and 0.975, '.' denotes 0.05 and 0.95 quantiles with the same sign.
Author(s)
Peter Rossi, Anderson School, UCLA, perossichi@gmail.com.
See Also
Examples
x = matrix(rnorm(1000), 100, 10)
y = x %*% rnorm(10) + rnorm(100)
fit=bayeslm(y~x)
summary(fit$beta)