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Simulate a from a Poisson process

Usage

rxPp(
  n,
  lambda,
  gamma = 1,
  prob = NULL,
  t0 = 0,
  tmax = Inf,
  randomOrder = FALSE
)

Arguments

n

Number of time points to simulate in the Poisson process

lambda

Rate of Poisson process

gamma

Asymmetry rate of Poisson process. When gamma=1.0, this simulates a homogenous Poisson process. When gamma<1.0, the Poisson process has more events early, when gamma > 1.0, the Poisson process has more events late in the process.

When gamma is non-zero, the tmax should not be infinite but indicate the end of the Poisson process to be simulated. In most pharamcometric cases, this will be the end of the study. Internally this uses a rate of:

l(t) = lambdagamma(t/tmax)^(gamma-1)

prob

When specified, this is a probability function with one argument, time, that gives the probability that a Poisson time t is accepted as a rejection time.

t0

the starting time of the Poisson process

tmax

the maximum time of the Poisson process

randomOrder

when TRUE randomize the order of the Poisson events. By default (FALSE) it returns the Poisson process is in order of how the events occurred.

Value

This returns a vector of the Poisson process times; If the dropout is >= tmax, then all the rest of the times are = tmax to indicate the dropout is equal to or after tmax.

Author

Matthew Fidler

Examples


## Sample homogenous Poisson process of rate 1/10
rxPp(10, 1 / 10)
#>  [1]   5.323784  21.415131  37.478421  40.945143  59.422799  85.409544
#>  [7] 102.011935 129.996616 142.404753 154.641998

## Sample inhomogenous Poisson rate of 1/10

rxPp(10, 1 / 10, gamma = 2, tmax = 100)
#>  [1] 26.07947 33.48687 54.82623 58.40640 60.65105 60.98144 61.70869 62.79017
#>  [9] 67.64753 76.77842

## Typically the Poisson process times are in a sequential order,
## using randomOrder gives the Poisson process in random order

rxPp(10, 1 / 10, gamma = 2, tmax = 10, randomOrder = TRUE)
#>  [1] 10 10 10 10 10 10 10 10 10 10

## This uses an arbitrary function to sample a non-homogenous Poisson process

rxPp(10, 1 / 10, prob = function(x) {
  1/(1+abs(x))
})
#>  [1]   0.4752658 147.5966580 186.9155552 205.7920579 220.3607906 305.9780282
#>  [7] 361.3626502 404.7342404 606.5618198 690.6836285