To this end, a Monte Carlo method (the switching-algorithm) is used to sample simulated datasets under a null model that preserves patient- and gene-wise mutation rates.
To evaluate different demographic scenarios (e.g. constant population sizes or population expansion from the time of the prehistoric sample), we simulated an extant sample and a prehistoric sample using the program COMPASS [ 17].
This research investigated adsorption kinetics and diffusion behaviour of decarbomoyl saxitoxin (dc-STX) and carbamate saxitoxin (STX) on a GAC sample and simulated a full-scale GAC filter using batch experimental data and the homogeneous surface diffusion model (HSDM).
For each dataset, and for a range of sub-sample sample sizes, we simulated a case control study and the two two-phase designs described above.
Sekine conducted shock-wave experiments by using a propellant gun that accelerated a stainless-steel disc into a composite sample simulating the components of meteorites, the ocean, and the atmosphere.
We performed 10 000 simulations where we simulated a sample of 17 374 individuals where the minor allele frequency (MAF = 0.39) and effect size (β = −0.082) were the same as LCT variant found in this study.
For each of the RAND, REGVAR and 2REG strategies, a random sampling process is simulated a thousand times.
In order to test whether specialization estimates are dependent on sampling and scale effects, we simulated a decreased sampling intensity in both networks using rarefaction (see Methods: Simulation of sampling effort and matrix architecture).
Then it was numerically solved by considering CH4 CO2 counter-diffusion and flow in a large coal sample to simulate a laboratory CO2-injection core flush experiment.
As we simulated a sample of 1000 effect curves based on the distribution of EFs, we can calculate risk as the fraction of those simulations where Effect(t) n exceeds 50% (Scheme 1, step 6).
