# Simulations for the Liland distribution.

### Description

Three different simulations are provided for the Liland distribution. These include sampling repeatedly from a given Liland distribution, sampling from the Bernoulli distribution and summarizing, and sampling random mean Liland numbers.

### Usage

1 2 3 | ```
simLiland(S, R, r)
simLiland2(S, R, r)
simLilandMu(S, R, r)
``` |

### Arguments

`S` |
number of samples. |

`R` |
number of trials or denominator of Bernoulli probability. |

`r` |
number of successes or numerator of Bernoulli probablity. |

### Value

`simLiland`

returns a vector of simulated Liland probabilities.
`simLiland2`

returns a list of sampled counts (`res`

),
summary of counts (`counts`

) and order of counts (`ms`

).
`simLilandMu`

returns a vector of simulated mean Liland numbers.

### Author(s)

Kristian Hovde Liland

### References

Liland, KH & Snipen, L, FixedTimeEvents: An R package for the distribution of distances between discrete events in fixed time, SoftwareX, in press.

### See Also

`dLiland`

, `Liland`

, `Liland.test`

### Examples

1 2 3 4 | ```
simLiland(1000,20,10)
sl <- simLiland2(1000,20,10)
sl$counts[sl$ms]/1000
plot(density(simLilandMu(1000,20,10)))
``` |