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Used to simulate data Used in analysis of simulated data Used to simulate data Used in analysis of simulated data The analyses produced PLL values for BS t and BN models of -47,006 and -48,006 respectively.
The uncertainty model, associated anchor points, and stochastic estimator was further applied to a software simulation whereby a variety of remote-sensing data sources were used to simulate data capture from legacy data sources.
These two models could then be combined and used to simulate data with spatial and temporal distribution of fruit matching those observed on Barro Colorado Island.
The parameteric estimates from the model were used to simulate data in line with the assumptions contained in the CJS models (individuals were independent and no overdispersion of data occurred).
These models were then used to simulate data in an interpolative manner across fibronectin concentrations and used in the classification.
For the purpose of inference, the model is generally used to simulate data other than observed data.
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Also incidence data were used to simulate prevalence data, and prediction models were developed to predict incidence from prevalence and from other relevant variables.
Consequently, when the true model is fitted to these data, all parameter estimates used to simulate the data are recovered exactly.
For the purpose of simulation, the forward evolutionary simulation tool ForSim [ 26] was used to simulate genotypic data within pedigrees.
It was used to simulate different data nodes that extend from 10000 to 50000.
The SIMIND Monte Carlo program [11] together with the XCAT phantom [12] was used to simulate projection data.
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