All functions

akde()

Calculate an autocorrelated kernel density estimate

as.telemetry() summary(<telemetry>) head() tail() tbind()

Import, coerce, summarize, and combine MoveBank data

bandwidth()

Calculate the optimal bandwidth matrix of movement data

buffalo

African buffalo GPS dataset from Kruger National Park, South Africa.

cluster()

Clustering of movement-model parameters

coati

Coatis on Barro Colorado Island, Panama.

annotate() color()

Color telemetry objects by time

ctmm-FAQ

ctmm FAQ

ctmm-package

Continuous-time movement modeling

ctmm.boot()

Parametric bootstrap continuous-time movement models

ctmm() ctmm.loglike() ctmm.fit() ctmm.select()

Specify, fit, and select continuous-time movement models

distance()

Calculate the square distance between two stationary distributions

emulate()

Draw a random model-fit from the sampling distribution

encounter()

Calculate the conditional location distribution of ecounters

as.sf() SpatialPoints.telemetry() SpatialPointsDataFrame.telemetry() SpatialPolygonsDataFrame.telemetry() SpatialPolygonsDataFrame.UD() raster(<UD>) writeShapefile() writeRaster(<UD>,<character>)

Export ctmm data formats

extent(<telemetry>) extent(<ctmm>) extent(<UD>) extent(<variogram>) extent(<list>) extent(<data.frame>) extent(<matrix>)

Extent

gazelle

Mongolian gazelle GPS dataset from the Mongolia's Eastern Steppe.

homerange()

Calculate a range distribution estimate

jaguar

Jaguar data from the Jaguar movement database.

mean(<UD>)

Average autocorrelated kernel density estimates

mean(<variogram>)

Compute a number-weighted average of variogram objects

meta()

Meta-analysis of movement-model parameters

occurrence()

Calculate a Kriged occurrence distribution estimate

optimizer()

Minimize a function

outlie() plot(<outlie>)

Methods to facilitate outlier detection.

overlap()

Calculate the overlap between two stationary distributions

pelican

Brown Pelican GPS and ARGOS data.

periodogram() plot(<periodogram>)

Calculate the Lomb-Scargle periodogram of animal-tracking data

plot() zoom(<list>) zoom(<telemetry>) zoom(<UD>)

Plotting methods for telemetry objects.

plot(<variogram>) zoom(<variogram>)

Plotting methods for variogram objects.

projection(<telemetry>) projection(<ctmm>) projection(<UD>) projection(<list>) projection(<NULL>) `projection<-`(<telemetry>) `projection<-`(<list>) median(<telemetry>) compass()

Projection

residuals(<ctmm>) residuals(<telemetry>) correlogram() mag()

Calculate model fit residuals and assess their autocorrelation

lasso() marquee() cleave()

Spatial selection methods for telemetry objects.

predict() simulate()

Predict or simulate from a continuous-time movement model

speed() speeds()

Estimate the average speed of a tracked animal

summary(<UD>)

Summarize a range distribution

summary(<ctmm>)

Summarize a continuous-time movement model

turtle

Wood turtle GPS and calibration dataset from Working Land and Seascapes.

uere() `uere<-`() uere.fit() summary(<UERE>)

Estimate RMS UERE from calibration data

`%#%`

Convert dimensionful quantities to and from SI units

variogram()

Calculate an empirical variogram from movement data

ctmm.guess() variogram.fit()

Visually fit a movement model to a variogram

video()

Video record animated telemetry objects.

wolf

Maned wolf GPS dataset from The Maned Wolf Conservation Program.