outlie.Rd
Produces a data.frame
of speed and distance estimates to analyze, as well as a plot highlighting potential speed and distance outliers in telemetry
data.
outlie(data,plot=TRUE,by='d',...) # S3 method for outlie plot(x,level=0.95,units=TRUE,axes=c('d','v'),...)
data 


plot  Output a plot highlighting high speeds (blue) and distant locations (red). 
by  Color and size sideeffect plot points by 
...  Arguments passed to 
x 

level  Confidence level for error bars. 
units  Convert axes to natural units. 
axes  \(x\)\(y\) axes to plot. Can be any of 
If plot=TRUE
in outlie()
, intervals of high speed are highlighted with blue segments, while distant locations are highlighted with red points.
When plotting the outlie
object itself, `core deviation' denotes distances from the median longitude & latitude, while `minimum speed' denotes the minimum speed required to explain the location estimate's displacement as straightline motion. Both estimates account for telemetry error and condition on as few data points as possible. The speed estimates furthermore account for timestamp truncation and assign each timestep's speed to the most likely offending time, based on its other adjacent speed estimate.
The output outlie
object contains the above noted speed and distance estimates in a data.frame
, with rows corresponding to those of the input telemetry
object.
Returns a data.frame
of distances and speeds. Can also produce a plot as a side effect.
C. H. Fleming et al, ``A comprehensive framework for handling location error in animal tracking data'', bioRxiv 2020.06.12.130195 (2020) doi: 10.1101/2020.06.12.130195 .
C. H. Fleming.
The speed estimates here are tailored for outlier detection and have poor statistical efficiency. The predict
and speed
methods are appropriate for estimating speed (after outliers have been removed and a movement model has been selected).
In ctmm
v0.6.1 the UERE
argument was deprecated. For uncalibrated data, the initial esitmates used by outlie
are now generated on import and stated by summary(uere(data))
. These values not be reasonable for arbitrary datasets.