speed: Estimate the average speed of a tracked animal

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

View source: R/1.R

Description

Given a ctmm movement model and telemetry data, speed simulates multiple realizations of the animal's trajectory and estimates the average speed, which is proportional to distance traveled. Both tortuosity (non straight-line motion between the data) and telemetry error can be accounted for. Given only a ctmm movement model and no data, speed calculates the average speed of the Gaussian movement process.

Usage

1
2
3
4
5
6
7
8
9
speed(object,...)

## S3 method for class 'ctmm'
speed(object,data=NULL,level=0.95,robust=FALSE,units=TRUE,prior=TRUE,fast=TRUE,
      cor.min=0.5,dt.max=NULL,error=0.01,cores=1,...)

## S3 method for class 'telemetry'
speed(object,CTMM,level=0.95,robust=FALSE,units=TRUE,prior=TRUE,fast=TRUE,
      cor.min=0.5,dt.max=NULL,error=0.01,cores=1,...)

Arguments

object

A ctmm movement-model or telemetry object, which requires an additional CTMM argument.

data

Optional telemetry object on which the simulations will be conditioned.

CTMM

Movement model object.

level

Confidence level to report on the estimated average speed.

robust

Use robust statistics for the ensemble average and its confidence intervals (see Details).

units

Convert result to natural units.

prior

Account for model uncertainty.

fast

Whether or not to invoke the central-limit theorem (see emulate).

cor.min

Velocity correlation threshold for skipping gaps.

dt.max

Absolute gap sizes to skip (in seconds), alternative to cor.min.

error

Target (relative) standard error.

cores

Number of simulations to run in parallel. cores=NULL will use all cores, while cores<0 will reserve abs(cores).

...

Arguments passed to emulate.

Details

The cor.min or dt.max arguments are used to constrain the estimate to be derived from simulations near the data, and therefore ensure that the estimate is more reflective of the data than the model.

If data quality is poor and velocity can barely be resolved, then the sampling distribution may occassionally include impersistent motion and the ensemble mean will be infinite. In these cases robust=TRUE can be used to report the ensemble median rather than the ensemble mean. The time average, in either case, is still the mean and the resulting quantity is still proportional to distance traveled. Furthermore, note that medians should be compared to medians and means to means, so the robust option should be the same for all compared individuals.

Value

Returns the estimated mean speed of the sampled trajectory with CIs by default. If level=NULL, then the ensemble of mean speeds is returned instead.

Note

The average speeds estimated here are mean speeds. The speeds reported by summary.ctmm are root-mean-square (RMS) speeds. These quantities are sometimes proportional, but not equivalent.

Author(s)

C. H. Fleming.

See Also

emulate, simulate

Examples

 1
 2
 3
 4
 5
 6
 7
 8
 9
10
11
12
13
# Load package and data
library(ctmm)
data(buffalo)
Cilla <- buffalo$Cilla

GUESS <- ctmm.guess(Cilla,interactive=FALSE)
FIT <- ctmm.fit(Cilla,GUESS)

# stationary Gaussian estimate
speed(FIT)

# conditional estimate
speed(FIT,Cilla)

ctmm-initiative/ctmm documentation built on Aug. 16, 2018, 6:50 a.m.