Burn-in included the first 100,000 generations for the 13-protein, all combined, and partial combined data sets, whereas the first 50,000 generations were discarded for the 4-protein, and allnuc data sets.
The first 10 volumes of each functional time series were discarded for the magnetization equilibrium.
The use of colostrum indicates a change from Lao traditional postpartum practices in which colostrum is discarded and the first breast feed delayed for 2 3 days [ 19].
Where a conversation sample was 10 min in length or longer, the first 5 min was discarded, with the second 5 min selected for analysis to maximise ecological validity.
The first BP reading was discarded and the second and third BP measurements were averaged for all the analyses.
The first 5,000 samples were discarded for burn-in, allowing the model to converge.
We ran three independent Markov chains for 100,000 iterations, discarded the first 5,000 iterations as a burn-in period (i.e. when the outputs are still affected by the choice of the arbitrary starting points of the chains and hence unrepresentative of the target posterior distribution), and thinned the remainder by 1 in 200.
We ran our Gibbs sampler for 12,000 iterations, discarded the first 10,000 samples as burn-in, and collected 1000 posterior samples with a thinning rate of two.
We set the prior hyperparameters as above and ran our Gibbs sampler for 40,000 iterations, discarded the first 20,000 samples as a burn-in period, and collected 1000 posterior samples of all parameters with a thinning rate of 20.
For each sequence, we discarded the first 6 volumes to allow for T1 equilibration effects, leaving 126 volumes for further analysis.
