Description Usage Arguments Value References See Also Examples

A binomial test is performed using probabilites from the Liland distribution to check
if the number of distances shorter to or equal to `xlim`

are significantly
higher than the expected value. Critical value and power are supplied as separate functions.

1 2 3 4 5 6 7 | ```
Liland.test(y, xlim, R, r)
## S3 method for class 'Ltest'
print(x, ...)
## S3 method for class 'Ltest'
summary(object, ...)
Liland.crit(xlim, R, r, alpha = 0.05)
Liland.pow(xlim, R, r, y = 1:(r-1), alpha = 0.05)
``` |

`y` |
The number of observed short distances. |

`xlim` |
The maximum distance that is seen as short. |

`R` |
The number of trials. |

`r` |
The number of successes. |

`alpha` |
Significance level. |

`x` |
The object to printed. |

`object` |
The object to be summarized. |

`...` |
Additional arguments for print and summary (not used). |

`Liland.test`

returns a named vector of P-values with class `Ltest`

. The other methods only print.

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

1 2 3 4 5 6 7 8 9 | ```
Lt <- Liland.test(12,1,1949,162)
print(Lt)
summary(Lt)
# Critical value
Liland.crit(1, 1949, 162)
# Power
plot(Liland.pow(1,1949,161, alpha = 0.05), type = 'l', xlab = '#(x<2)', ylab = 'power')
``` |

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