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References

S.P Brooks.
Quantitative convergence diagnosis for mcmc via cusums.
Technical report, University of Bristol, 1997.

S.P. Brooks and A. Gelman.
Alternative methods for monitoring convergence of iterative simulations.
Computational and Graphical Statistics, 1997.

S.P. Brooks and A. Gelman.
Some issues in monitoring convergence of iterative simulations.
Technical report, University of Bristol, 1998.

S.P. Brooks and G.O. Roberts.
Assessing convergence of markov chain monte carlo algorithms.
Statistics and Computing, 1998.

Andrew Gelman, John B. Carlin, Hal S. Stern, and Donald R. Rubin.
Bayesian Data Analysis.
Texts in Statistical Science. Chapman & Hall, 1995.

Radford M. Neal.
Bayesian Learning for Neural Networks, volume 118 of Lecture Notes in Statistics.
Springer-Verlag, 1996.

A.E. Raftery and S.M. Lewis.
How many iterations in the gibbs sampler.
Technical report, 1991.

B. Yu.
Estimating l1 error of kernel estimator: Monitoring convergence of markov samplers.
Technical report, Dept. of Statistics. University of California, Berkeley, 1995.

B. Yu and Mykland P.
Looking at markov samplers through cusum path plots: a simple diagnostic idea.
Statistics and Computing, 1997.



Simo Särkkä
8/23/1999