I have model with 20000 latent parameters, set up in a Gibb's sampler.
98% of the parameters and sometimes 99.5% of the parameters satisfy the Geweke convergence statistic, have low autocorrelation at a lag of 10 and have a good effective sample size.
My parameters of interest are in the 98%. Running the chain to 100000 iterations doesn't really change much. What are my options?
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