View source: R/plot.variogram.R
plot.variogram | R Documentation |
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.
## 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,...)
x |
A |
CTMM |
A |
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, |
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 |
... |
Additional |
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
.
The errors of the empirical variogram are correlated. Smooth trends are not necessarily significant.
J. M. Calabrese and C. H. Fleming
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) \Sexpr[results=rd]{tools:::Rd_expr_doi("10.1086/675504")}.
correlogram
, ctmm.fit
, plot
, variogram
, variogram.fit
.
# 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)
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.