Set the parallel seed for rxode2 random number generationSource:
This sets the seed for the rxode2 parallel random number generation. If set, then whenever a seed is set for the threefry or vandercorput simulation engine, it will use this seed, increment for the number of seeds and continue with the sequence the next time the random number generator is called.
An integer that represents the rxode2 parallel and internal random number generator seed. When positive, use this seed for random number generation and increment and reseed any parallel or new engines that are being called. When negative, turn off the rxode2 seed and generate a seed from the R's uniform random number generator. Best practice is to set this seed.
In contrast, when this is not called, the time that the vandercorput or threefry simulation engines are seeded it comes from a uniform random number generated from the standard R random seed. This may cause a duplicate seed based on the R seed state. This means that there could be correlations between simulations that do not exist This will avoid the birthday problem picking exactly the same seed using the seed state of the R random number generator. The more times the seed is called, the more likely this becomes.
JD Cook. (2016). Random number generator seed mistakes. https://tinyurl.com/m62v3kv9
rxSetSeed(42) # seed with generator 42 rxnorm() #>  0.2229005 # Use R's random number generator rnorm(1) #>  0.04863385 rxSetSeed(42) # reproduces the same number rxnorm() #>  0.2229005 # But R's random number is not the same rnorm(1) #>  1.220873 # If we reset this to use the R's seed # (internally rxode2 uses a uniform random number to span seeds) # This can lead to duplicate sequences and seeds rxSetSeed(-1) # Now set seed works for both. # This is not recommended, but illustrates the different types of # seeds that can be generated. set.seed(42) rxnorm() #>  -0.6306035 rnorm(1) #>  -0.5646982 set.seed(42) rxnorm() #>  -0.6306035 rnorm(1) #>  -0.5646982