Currently I’ve fitted the data with a model through 4 chains and 1000 iterations: no warnings, all Rhat of 1.0. I guess the resulting 2000 posterior samples are good enough to obtain the central 95% posterior interval.
Suppose that I would like to obtain the central 99% posterior interval. How many samples would be considered reasonable? Is it valid to obtain more samples by simply increasing the numbers of chains:
for example, 20 chains with 1000 iterations for 10,000 samples?