ctmm (version 0.3.6)

summary.ctmm: Summarize a continuous-time movement model

Description

This function returns a list of biologically interesting parameters in human readable format, as derived from a continuous-time movement model.

Usage

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

Arguments

object

A ctmm movement-model object from the output of ctmm.fit.

level

Confidence level for parameter estimates.

level.UD

Confidence level for the Gaussian home-range area.

units

Convert result to natural units.

IC

Information criteria for sorting lists of ctmm objects.

...

Unused options.

Value

If summary is called with a single ctmm object output from ctmm.fit, then a list is returned with effective sample size array DOF and parameter estimate table CI, with low, maximum likelihood, and high estimates for the following possible parameters:

tau

The autocorrelation timescales.

area

The Gaussian home-range area, where the point estimate has a significance level of level.UD. I.e., the core home range is where the animal is located 50% of the time with level.UD=0.50. This point estimate itself is subject to uncertainty, and is given confidence intervals derived from level.

speed

The Gaussian root-mean-square (RMS) velocity, which is a convenient measure of average speed.

If summary is called on a list of ctmm objects output from ctmm.select, then a table is returned with the model names and AIC differences, where "IID" denotes the uncorrelated bi-variate Gaussian model, "OU" denotes the continuous-position Ornstein-Uhlenbeck model, and "OUF" denotes the continuous-velocity Ornstein-Uhlenbeck-F model.

See Also

ctmm.fit, ctmm.select.

Examples

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

# Extract movement data for a single animal
cilla <- buffalo[[1]]

# Find the best OU movement model
# also see help(variogram.fit)
GUESS <- ctmm(tau=60*60*24*10)
FIT <- ctmm.fit(cilla,GUESS)

# Tell us something interpretable
summary(FIT)
# }