Compute the standard errors for the Bayes factors estimates.
1 2 
pargrid 
A data frame with components "linkp", "phi", "omg", "kappa". Each row gives a combination of the parameters to compute the new standard errors. 
runs 
A list with outputs from the function

nbatches 
An integer scalar or vector of the same length as runs indicating the number of batches to create for computing the variance using the samples of the first stage. 
bfsize1 
A scalar or vector of the same length as

method 
Which method to use to calculate the Bayes factors: Reverse logistic or MengWong. 
reference 
Which model goes in the denominator. 
transf 
Whether to use the transformed sample mu for the computations. Otherwise it uses z. 
bmmcse.size 
Size for computing the batch means MonteCarlo variance using the samples of the second stage. 
Uses the batch means method to compute the standard errors for Bayes factors.
A list with components
pargrid
The inputted pargrid augmented with the computed standard
errors.
bfEstimate
The estimates of the Bayes factors
bfSigma
The covariance matrix for the Bayes factors
estimates.
Roy, V., Tan, A. and Flegal, J. (2015). Estimating standard errors for importance sampling estimators with multiple Markov chains. Technical report, Iowa State University. http://lib.dr.iastate.edu/stat_las_preprints/34
Questions? Problems? Suggestions? Tweet to @rdrrHQ or email at ian@mutexlabs.com.
Please suggest features or report bugs with the GitHub issue tracker.
All documentation is copyright its authors; we didn't write any of that.