Monitoring Convergence in High Dimensions continued
In my last posting I introduced a program for comparing different methods of convergence assessment in multi-dimensional MCMC analyses. Essentially the program samples from an imaginary posterior that takes the form of a user specified mixture of multivariate normal distributions. Previously, I illustrated some of the problems of assessing convergence by looking at a simulated […]
Monitoring Convergence in High Dimensions
In Chapter 5 of ‘Bayesian Analysis with Stata’ I discussed methods for monitoring the convergence of a set of MCMC simulations. Obviously it is important to demonstrate the effectiveness of different approaches to the assessment of convergence using output from real MCMC analyses, but often real problems are difficult to judge because we do not know the exact truth […]
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