Uncertainty quantification in numerical simulations generally relies on applying sampling techniques to select input parameters for a suite of deterministic calculations and then combining the results of the calculations into output distributions. Several approaches, including metamodeling and Latin Hypercube Sampling, are prevalent today. This paper will focus on the comparison of several comm...

We have investigated decorrelation of samples in quantum Monte Carlo ground-state energy calculations for large Li and H2O nanoclusters. Binning data as a way of eliminating statistical correlations, as is the common practice, is found to become increasingly impractical as the system size grows. We demonstrate nevertheless that it is possible to perform accurate energy calculations—without deco...

The most common statistical pitfalls in ecological research are those associated with data exploration, the logic of sampling and design, and the interpretation of statistical results. Although one can find published errors in calculations, the majority of statistical pitfalls result from incorrect logic or interpretation despite correct numerical calculations. There are often simple solutions ...

background: the monte carlo (mc) method is not only used for dose calculations around brachytherapy sources but also for benchmarking treatment planning systems (tps) calculations. materials and methods: three 60co sources of gzp6 brachytherapy unit were simulated using mcnp4c mc code. the radial dose functions were calculated by mc method and gzp6 tps and were compared. results: there was a go...