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8.8.5 Location LOD scores MCMC parameters and options

Additional statements for lm_bayes include the following:

set preliminary iterations I

Following burn-in, lm_bayes performs preliminary iterations to calculate the pseudo-priors. These pseudo-priors are used to encourage the MCMC sampler to visit test positions of low posterior probability.

set sequential imputation proposals every I iterations

This option applies to lm_bayes's preliminary and main MCMC iterations. It allows the MCMC chain to "restart" every Ith iteration. Sequential imputation is used to propose potential restart configurations which are accepted/rejected with Metropolis-Hastings probability.

set test position window I

This lm_bayes statement specifies the window size for the Metropolis-Hastings algorithm. I is the number of hypothesized trait positions on either side of the current position, with equal weight given to the 2*I + 1 trait positions. The default is window size is 6.



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