For the Bayesian population modeling, we ran eight independent MCMC chains, each to 160,000 iterations, with the first half discarded as "burn-in" iterations.
In order to validate this simulation model, we run the model based on actual cargo retrieval schedules obtained from an air cargo terminal.
For each model, we run a regression of SDS on all remaining parameters and include residuals of these routines as an additional variable in the models.
To verify the sediment transport model, we run numerical simulation of sediment transported by the 2004 Indian Ocean tsunami in Lhok Nga, Banda Aceh, Indonesia.
To check the convergence of the iBAG unified model, we run two MCMC chains with different starting values.
During the bound testing of these 3 models, we ran each model by considering each variable as the dependent variable to investigate the long-run cointegration.
Regarding the choice of compartment model, we ran the curve fitting algorithm on all tissue data using four different models: 1T1k+Vb, 1T2k+Vb, 2T3k+Vb, and 2T4k+Vb.
Accordingly, we ran three models: the first two used the liberal classification for accuracy (and replicated the models we ran in Experiment 1), and the other examined the more stringent classification, DL.
In order to test whether or to what extent the near-field coseismic GPS displacements can be explained by seismic source model, we ran forward modeling using Ji and Hayes' slip model (Fig. 5).
For each of the two AGC models, we ran 1000 iterations of RF that included the <0.85 correlated preliminary set of LiDAR metrics to create distributions of MIR for each metric.
