rxnorm(mean = 0, sd = 1, n = 1L, ncores = 1L)

rxnormV(mean = 0, sd = 1, n = 1L, ncores = 1L)

## Use threefry engine

rxnorm(n=10) # with rxnorm you have to explicitly state n
rxnorm(n=10,ncores=2) # You can parallelize the simulation using openMP

rxnorm(2,3) ## The first 2 arguments are the mean and standard deviation


## This example uses `rxnorm` directly in the model

rx <- RxODE({
  a = rxnorm()
})

et <- et(1,id=1:2)

s <- rxSolve(rx,et)

## Use vandercorput generator

rxnormV(n=10) # with rxnorm you have to explicitly state n
rxnormV(n=10,ncores=2) # You can parallelize the simulation using openMP

rxnormV(2,3) ## The first 2 arguments are the mean and standard deviation


## This example uses `rxnormV` directly in the model

rx <- RxODE({
  a = rxnormV()
})

et <- et(1,id=1:2)

s <- rxSolve(rx,et)