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

This function calculates autocorrelated kernel density home-range estimates from `telemetry`

data and a corresponding continuous-time movement model.

1 2 3 4 5 6 7 8 9 10 | ```
akde(data,CTMM,VMM=NULL,debias=TRUE,smooth=TRUE,error=0.001,res=10,grid=NULL,...)
## S3 method for class 'telemetry'
akde(data,CTMM,VMM=NULL,debias=TRUE,smooth=TRUE,error=0.001,res=10,grid=NULL,...)
## S3 method for class 'list'
akde(data,CTMM,VMM=NULL,debias=TRUE,smooth=TRUE,error=0.001,res=10,grid=NULL,...)
## S3 method for class 'UD'
mean(x,...)
``` |

`data` |
2D timeseries telemetry data represented as a |

`CTMM` |
A |

`VMM` |
An optional vertical |

`debias` |
Debias the distribution for area estimation (AKDEc). |

`smooth` |
"Smooth" out errors from the data. |

`error` |
Target probability error. |

`res` |
Number of grid points along each axis, relative to the bandwidth. |

`grid` |
Optional grid specification with columns labeled |

`...` |
Arguments passed to all instances of |

`x` |
A list of |

Returns a `UD`

object: a list with the sampled grid line locations `r$x`

and `r$y`

, the extent of each grid cell `dr`

, the probability density and cumulative distribution functions evaluated on the sampled grid locations `PDF`

& `CDF`

, the optimal bandwidth matrix `H`

, and the effective sample size of the data in `DOF.H`

.

For weighted AKDE, please note additional `...`

arguments passed to `bandwidth`

and the `weights=TRUE`

argument, specifically.

When feeding in lists of `telemetry`

and `ctmm`

objects, all UDs will be calculated on the same grid. These UDs can be averaged with the `mean`

command, however this is not an optimal way to calculate population ranges.

In the case of coarse grids, the value of `PDF`

in a grid cell corresponds to the average probability density over the entire rectangular cell.

Prior to `ctmm`

v0.3.2, the default AKDE method was the autocorrelated Gaussian reference function bandwidth.
Starting in v0.3.2, the default AKDE method is the autocorrelated Gaussian reference function bandwidth with debiased area.

Prior to `ctmm`

v0.3.1, AKDEs included only errors due to autocorrelation uncertainty, which are insignificant in cases such as IID data.
Starting in v0.3.1, `akde`

calculated an effective sample size `DOF.H`

and used this to estimate area uncertainty under a Gaussian reference function approxmation.
In v0.3.2, this method was further improved to use `DOF.area`

from the Gaussian reference function approximation.

C. H. Fleming and K. Winner.

C. H. Fleming, W. F. Fagan, T. Mueller, K. A. Olson, P. Leimgruber, J. M. Calabrese. Rigorous home-range estimation with movement data: A new autocorrelated kernel-density estimator. Ecology, 96:5, 1182-1188 (2015).

C. H. Fleming, J. M. Calabrese. A new kernel-density estimator for accurate home-range and species-range area estimation. Methods in Ecology and Evolution, 8:5, 571-579 (2016).

1 2 3 4 5 6 7 8 9 10 11 12 13 |

ctmm documentation built on Aug. 30, 2017, 5:07 p.m.

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