In the call to haplo.score, the sim.control parameter is a list of parameters that control the simulations. This list is created by this function, score.sim.control, making it easy to change the default values.
score.sim.control(p.threshold=0.25, min.sim=1000, max.sim=20000.,verbose=FALSE)A list of the control parameters:
As described above
As described above.
As described above
As described above
A paremeter used to determine p-value precision from Besag and Clifford (1991). For a p-value calculated after min.sim simulations, continue doing simulations until the p-value's sample standard error is less than p.threshold * p-value. The dafault value for p.threshold = 1/4 corresponds approximately to having a two-sided 95% confidence interval for the p-value with a width as wide as the p-value itself. Therefore, simulations are more precise for smaller p-values. Additionally, since simulations are stopped as soon as this criteria is met, p-values may be biased high.
The minimum number of simulations to run. To run exactly min.sim simulations, set max.sim = min.sim. Also, if run-time is an issue, a lower minimum (e.g. 500) may be useful, especially when doing simulations in haplo.score.slide.
The upper limit of simulations allowed. When the number of simulations reaches max.sim, p-values are approximated based on simulation results at that time.
Logical, if (T)rue, print updates from every simulation to the screen. If (F)alse, do not print these details.
In simulations for haplo.score, employ the simulation p-value precision criteria of Besag and Clifford (1991). The criteria ensures both the global and the maximum score statistic simulated p-values be precise for small p-values. First, perform min.sim simulations to guarantee sufficient precision for the score statistics on individual haplotypes. Then continue simulations as needed until simulated p-values for both the global and max score statistics meet precision requirements set by p.threshold.
Besag, J and Clifford, P. "Sequential Monte Carlo p-values." Biometrika. 78, no. 2 (1991): 301-304.
haplo.score
# it would be used in haplo.score as appears below
#
# score.sim.500 <- haplo.score(y, geno, trait.type="gaussian", simulate=T,
# sim.control=score.sim.control(min.sim=500, max.sim=2000)
Run the code above in your browser using DataLab