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

Function to discriminate between periods of residency and movement based on
consecutive sunrise and sunset data. The calculation is based on a
changepoint model (**R** Package `changepoint`

:
`cpt.mean`

) to find multiple changepoints within the
data.

1 2 |

`tFirst` |
vector of sunrise/sunset times (e.g. 2008-12-01 08:30). |

`tSecond` |
vector of of sunrise/sunset times (e.g. 2008-12-01 17:30). |

`type` |
vector of either 1 or 2, defining |

`twl` |
data.frame containing twilights and at least |

`quantile` |
probability threshold for stationary site selection. Higher
values (above the defined quantile of all probabilities) will be considered
as changes in the behavior. Argmuent will only be considered if either |

`rise.prob` |
the probability threshold for |

`set.prob` |
the probability threshold for |

`days` |
a threshold for the length of stationary period. Periods smaller than "days" will not be considered as a residency period |

`plot` |
logical, if |

`summary` |
logical, if |

The `cpt.mean`

from the `R`

Package `changepoint`

is a
function to find a multiple changes in mean for data where no assumption is
made on their distribution. The value returned is the result of finding the
optimal location of up to Q changepoints (in this case as many as possible)
using the cumulative sums test statistic.

A `list`

with probabilities for *sunrise* and
*sunset* the user settings of the probabilities and the resulting
stationary periods given as a `vector`

, with the residency sites as
positiv numbers in ascending order (0 indicate movement/migration).

The sunrise and/or sunset times shown in the graph (if
`plot=TRUE`

) represent hours of the day. However if one or both of the
twilight events cross midnight during the recording period the values will
be formed to avoid discontinuity.

Simeon Lisovski & Tamara Emmenegger

Taylor, Wayne A. (2000) Change-Point Analysis: A Powerful New Tool For Detecting Changes.

M. Csorgo, L. Horvath (1997) Limit Theorems in Change-Point Analysis.
*Wiley*.

Chen, J. and Gupta, A. K. (2000) Parametric statistical change point
analysis. *Birkhauser*.

1 2 3 4 | ```
data(hoopoe2)
hoopoe2$tFirst <- as.POSIXct(hoopoe2$tFirst, tz = "GMT")
hoopoe2$tSecond <- as.POSIXct(hoopoe2$tSecond, tz = "GMT")
residency <- changeLight(hoopoe2, quantile=0.9)
``` |

```
Loading required package: maps
Probability threshold(s):
Sunrise: 0.02133 Sunset: 0.01307
Migration schedule table:
Site Arrival Departure Days P.start P.end
1 a 2008-07-15 23:34:00 2008-07-24 23:32:30 9.0 0.000000000 0.0000000000
2 b 2008-07-31 00:15:00 2008-08-19 12:26:00 19.5 0.010500257 0.0000000000
3 c 2008-08-25 00:25:30 2008-09-01 12:20:00 7.5 0.005555556 0.0069958848
4 d 2008-09-12 12:27:30 2008-10-02 12:28:00 20.0 0.000000000 0.0009259259
5 e 2008-10-03 12:22:30 2008-10-19 12:26:00 16.0 0.004629630 0.0010204082
6 f 2008-10-20 12:22:00 2008-11-15 00:13:30 25.5 0.003776042 0.0055555556
7 g 2008-11-16 00:21:30 2008-12-03 12:35:30 17.5 0.005555556 0.0061983471
8 h 2008-12-09 00:31:30 2008-12-18 12:32:00 9.5 0.000000000 0.0107060185
9 i 2008-12-19 12:41:00 <NA> NA 0.000000000 0.0000000000
Days.1 P.start.1
1 9.0 0.000000000
2 19.5 0.010500257
3 7.5 0.005555556
4 20.0 0.000000000
5 16.0 0.004629630
6 25.5 0.003776042
7 17.5 0.005555556
8 9.5 0.000000000
9 NA 0.000000000
```

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