baseline.parallel: Generate Distance Samples to Build Baseline Distribution...
In geoCount: Analysis and Modeling for Geostatistical Count Data

Description Usage Arguments Details Value Author(s) See Also Examples

This function generates distance samples in parallel to build the baseline distribution for standard normal.

1	baseline.parallel(n, iter, n.cores = getOption("cores"))

`n`	the number of residuals
`iter`	the number of distance samples to generate
`n.cores`	the number of CPUs that will be used for parallel computing

HellingerDist and KolmogorovDist functions in {distrEx} are used to compute the distances. See ?HellingerDist and ?KolmogorovDist for details about how the distances are computed.

This function performs parallel computing with the help of {multicore} package. Be aware that {multicore} package currently is not available in Windows.

A iter \times 3 matrix for three types of distance: "Discrete Hellinger", "Smooth Hellinger" and "Kolmogorov".

Liang Jing ljing918@gmail.com

d.base, baseline.dist, plot_baseline, pOne.

## Not run: 
# Time-consuming! Run once with large "iter" and 
# save the results for future use
require(multicore)
d.base <- baseline.parallel(50, iter=100, n.cores = 4) 
## End(Not run)