Summarize Mcmc Parameter Draws
summary.bayesm.mat is an S3 method to summarize marginal distributions given an array of draws
## S3 method for class 'bayesm.mat' summary(object, names, burnin = trunc(0.1 * nrow(X)), tvalues, QUANTILES = TRUE, TRAILER = TRUE,...)
object |
|
names |
optional character vector of names for the columns of |
burnin |
number of draws to burn-in (def: 0.1*nrow(X)) |
tvalues |
optional vector of "true" values for use in simulation examples |
QUANTILES |
logical for should quantiles be displayed (def: |
TRAILER |
logical for should a trailer be displayed (def: |
... |
optional arguments for generic function |
Typically, summary.bayesm.nmix will be invoked by a call to the generic summary function as in summary(object) where object is of class bayesm.mat. Mean, Std Dev, Numerical Standard error (of estimate of posterior mean), relative numerical efficiency (see numEff), and effective sample size are displayed. If QUANTILES=TRUE, quantiles of marginal distirbutions in the columns of X are displayed.
summary.bayesm.mat is also exported for direct use as a standard function, as in summary.bayesm.mat(matrix).
summary.bayesm.mat(matrix) returns (invisibly) the array of the various summary statistics for further use. To assess this array usestats=summary(Drawmat).
Peter Rossi, Anderson School, UCLA, perossichi@gmail.com.
## Not run: out=rmnpGibbs(Data,Prior,Mcmc); summary(out$betadraw)
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