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If high fly densities are needed for a comparatively long period, the size of the global search space prevents Gibbs optimization, because it requires too many sampling iterations.
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We used 750,000 burn-in iterations and 1,500,000 sampling iterations with a sampling period of 150.
We performed 1.5 million sampling iterations with a sampling period of 150 and burn-in iterations of 750,000.
Each simulation comprised 20,000 'burn-in' iterations followed by 40,000 posterior mean sample iterations.
We performed 1,000 Gibbs sampling iterations (tmax=1,000).
Runs had 10,000 burn-in iterations followed by 10,000 sampling iterations.
ClonalFrame was run with 50,000 burn in iterations and 50,000 sampling iterations.
Burn-in was 5000 Gibbs sampling iterations, and the number of iterations between each imputed dataset was 1000.
The sample distribution for the 500 sample iterations varied across sites.
MCMC consisted of 10 burn-in iterations followed by 10 sampled iterations.
All sampled iterations before convergence were discarded as burn-in.
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