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The main statistical advantage of copulas is in replicating datasets through simulation with any type of marginal distributions.
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Table 4 shows the average of the estimated parameters obtained from the 100 replicated datasets.
Posterior predictive p-values allow us to average over the uncertainty in θ and γ using M simulated replicated datasets (x∗) from the predictive distribution of the data.
A new MaxEnt model was fit to each of these 100 replicated datasets and used to create 100 full resolution biomass maps.
One hundred thousand replicated datasets were studied under Scenarios 2 to 4 and 10,000 under Scenario 1.
For bias evaluation the final model was fitted to replicate datasets using the bootstrap resampling technique in Wings for NONMEM [35], and PK parameter estimates and random effects for each of the replicate datasets were obtained.
In total, 25 replicated datasets were simulated.
Note that for the permutation tests we used 1000 replicated datasets and for other tests we used 5000 replicated datasets.
We run T-test on the observed dataset and the 1000 replicated datasets.
The outcomes of interest from the 500 replicated datasets were summarised using the average or median value where appropriate.
Hypothesis testing between accuracies of different methods were based on blocking on replicated datasets, using a Wilcoxon signed rank test.
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