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

Density, distribution function, quantile function and random generation
for the Liland distribution with `R`

trials and `r`

successes.

1 2 3 4 |

`x, q` |
vector of quantiles. |

`p` |
vector of probabilities. |

`n` |
number of observations. |

`R` |
number of trials. |

`r` |
number of successes. |

`warn` |
logical indicating if a warning should be issued if approximation is used. |

`lower.tail` |
logical indicating if the lower tail of the distribution should be summed. |

The Liland distribution has probability mass

*
f(X=x;R,r) = binomial(R-x|r-1)/binomial(R|r)
*

where *x* is the distance between consecutive successes, *R*
is the number of trials and *r* is the number of successes.

`dLiland`

gives the probability mass, `pLiland`

gives the distribution
function, `qLiland`

gives the quantile function, and `rLiland`

generates
random Liland values.

Kristian Hovde Liland

Liland, KH & Snipen, L, FixedTimeEvents: An R package for the distribution of distances between discrete events in fixed time, SoftwareX 5 (2016).

`Liland`

, `Liland.test`

, `simLiland`

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 | ```
dLiland(19, R = 1949, r = 162)
pLiland(19, R = 1949, r = 162)
qLiland(0.5, R = 1949, r = 162)
plot( pLiland(1:100, R = 1949, r = 162) )
## QQ-plot of Liland distribution and random Liland values
R <- 2000
r <- 120
n <- 1000
samp <- rLiland(n,R,r)
theo <- qLiland(ppoints(n),R,r)
qqplot(theo,samp,
xlab='F(x;2000,120)', ylab='Sample (1000)', axes=FALSE)
axis(1,at=c(0,40,80,120))
axis(2,at=c(0,40,80,120))
box()
qqline(samp, distribution = function(p)qLiland(p,R=2000,r=120), col='gray',lty=2)
``` |

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