`summary.UD.Rd`

This function returns a list of biologically interesting parameters in human readable format, as derived from an autocorrelated kernel density estimate.

# S3 method for UD summary(object,level=0.95,level.UD=0.95,units=TRUE,...)

object | An |
---|---|

level | Confidence level for the above area estimate. E.g., the 95% confidence interval of the 50% core area. |

level.UD | Coverage level for the home-range area. E.g., the 50% core area. |

units | Convert result to natural units. |

... | Unused options. |

A list is returned with the effective sample sizes of various parameter estimates (`DOF`

) and a parameter estimate table `CI`

, with low, point, and high estimates for the following possible parameters:

`area`

The home-range area with fraction of inclusion

`level.UD`

. E.g., the 50% core home range is estimated with`level.UD=0.50`

, and 95% confidence intervals are placed on that area estimate with`level=0.95`

.This kernel density estimate differs from the Gaussian estimate of`summary.ctmm`

. The Gaussian estimate has more statistical efficiency, but is less related to space use for non-Gaussian processes.

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) doi: 10.1111/2041-210X.12673 .

C. H. Fleming.

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 chi-square approxmation.
Starting in v0.3.2, this method was improved to use `DOF.area`

in the Gaussian reference function approximation.

`akde`

.

# \donttest{ # Load package and data library(ctmm) data(buffalo) # Extract movement data for a single animal Cilla <- buffalo$Cilla # Fit a movement model GUESS <- ctmm.guess(Cilla,interactive=FALSE) FIT <- ctmm.fit(Cilla,GUESS) # Estimate and summarize the AKDE UD <- akde(Cilla,FIT) summary(UD)#> $DOF #> area bandwidth #> 18.13598 29.23444 #> #> $CI #> low est high #> area (square kilometers) 223.4286 376.1535 568.009 #># }