ctmm (version 0.5.5)

outlie: Methods to facilitate outlier detection.

Description

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.

Usage

outlie(data,UERE=10,standardize=FALSE,plot=TRUE,...)

Arguments

data

telemetry object.

UERE

Device-dependent telemetry error in meters. Only necessary for uncalibrated data.

standardize

Standardize speed and distance output by their median absolute deviation (MAD).

plot

Output a plot highlighting high speeds (blue) and distant locations (red).

...

Arguments passed to plot.

Value

Returns a data.frame of distances and speeds. Can also produce a plot as a side effect.

Details

Distances are calculated from the median longitude & latitude, while speeds are calculated over the timesteps. 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.

If plot=TRUE, intervals of high speed are highlighted with blue segments, while distant locations are highlighted with red points.

See Also

as.telemetry.

Examples

# NOT RUN {
# Load package and data
library(ctmm)
data(buffalo)

# look for outliers in Cilla
OUT <- outlie(buffalo[[1]])

# look at the distribution of speed esitmates
hist(OUT$speed)
# }