plot.variogram {ctmm}

Plotting methods for variogram objects.

Description

Produces simple plots of varigram objects (semi-variance vs. time lag) and model semi-variance functions, with approximate confidence intervals around the semi-variance estimates.

Usage

## S3 method for class 'variogram'
plot(x,CTMM=NULL,level=0.95,units=TRUE,fraction=0.5,col="black",col.CTMM="red",xlim=NULL,
     ylim=NULL,ext=NULL,...)

## S4 method for signature 'variogram'
zoom(x,fraction=0.5,...)

Arguments

x

A variogram object calculated using variogram.

CTMM

A ctmm movement model object in the same format as the output of ctmm.fit or variogram.fit.

level

Confidence level of confidence bands (95% default CIs). Can be an array.

units

Convert axes to natural units.

fraction

The proportion of the variogram object, variogram, that will be plotted. By convention, half is shown. The tail end is generally garbage.

col

Color for the empirical variogram. Can be an array.

col.CTMM

Color for the model. Can be an array.

xlim

Range of lags to plot (in SI units).

ylim

Range of semi-variance to plot (in SI units).

ext

Plot extent alternative to xlim and ylim (see extent).

...

Additional plot function parameters.

Value

Returns a plot of semi-variance vs. time lag, with the empirical variogram in black and the ctmm semi-variance function in red if specified. zoom includes a log-scale zoom slider to manipulate fraction.

Note

The errors of the empirical variogram are correlated. Smooth trends are not necessarily significant.

Author(s)

J. M. Calabrese and C. H. Fleming

References

C. H. Fleming, J. M. Calabrese, T. Mueller, K.A. Olson, P. Leimgruber, W. F. Fagan. From fine-scale foraging to home ranges: A semi-variance approach to identifying movement modes across spatiotemporal scales. The American Naturalist, 183:5, E154-E167 (2014) doi:10.1086/675504.

See Also

correlogram, ctmm.fit, plot, variogram, variogram.fit.

Examples

# Load package and data
library(ctmm)
data(buffalo)

# Extract movement data for a single animal
Cilla <- buffalo$Cilla

# Calculate variogram
SVF <- variogram(Cilla)

# Plot the variogram
plot(SVF)