ctmm: plot.variogram – R documentation

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plot.variogram

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 blue 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.

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)

ctmm

Continuous-Time Movement Modeling

v0.6.0

GPL-3

Authors

Christen H. Fleming [aut, cre], Justin M. Calabrese [aut], Xianghui Dong [ctb], Kevin Winner [ctb], Guillaume Péron [ctb], Michael J. Noonan [ctb], Bart Kranstauber [ctb], Eliezer Gurarie [ctb], Kamran Safi [ctb], Paul C. Cross [dtc], Thomas Mueller [dtc], Rogério C. de Paula [dtc], Thomas Akre [dtc], Jonathan Drescher-Lehman [dtc], Autumn-Lynn Harrison [dtc], Ronaldo G. Morato [dtc]

Initial release

2021-01-08