This program computes the empirical variogram of a selected variable. If the coordinates are in decimal degrees, set latlon = TRUE. The program return a table with the mean class distances (d.mean) and the semivariances (obs) for each class.
eco.variogram(Z, XY, int = NULL, smin = 0, smax = NULL, nclass = NULL, seqvec = NULL, size = NULL, bin = c("sturges", "FD"), row.sd = FALSE, latlon = FALSE, angle = NULL)
| Z | Vector for the analysis. |
|---|---|
| XY | Data frame or matrix with the position of individuals (projected coordinates). |
| int | Distance interval in the units of XY. |
| smin | Minimum class distance in the units of XY. |
| smax | Maximum class distance iin the units of XY. |
| nclass | Number of classes. |
| seqvec | Vector with breaks in the units of XY. |
| size | Number of individuals per class. |
| bin | Rule for constructing intervals when a partition parameter (int, nclass or size) is not given. Default is Sturge's rule (Sturges, 1926). Other option is Freedman-Diaconis method (Freedman and Diaconis, 1981). |
| row.sd | Logical. Should be row standardized the matrix? Default FALSE (binary weights). |
| latlon | Are the coordinates in decimal degrees format? Defalut FALSE. If TRUE,
the coordinates must be in a matrix/data frame with the longitude in the first
column and latitude in the second. The position is projected onto a plane in
meters with the function |
| angle | Direction for computation of a bearing variogram (angle between 0 and 180). Default NULL (omnidirectional). |
The program returns an object of class "eco.correlog" with the following slots:
> OUT analysis output
> IN analysis input data
> BEAKS breaks
> CARDINAL number of elements in each class
> DISTMETHOD method used in the construction of breaks
ACCESS TO THE SLOTS The content of the slots can be accessed with the corresponding accessors, using the generic notation of EcoGenetics (<ecoslot.> + <name of the slot> + <name of the object>). See help("EcoGenetics accessors") and the Examples section below
Borcard D., F. Gillet, and P. Legendre. 2011. Numerical ecology with R. Springer Science & Business Media.
Legendre P., and L. Legendre. 2012. Numerical ecology. Third English edition. Elsevier Science, Amsterdam, Netherlands.
Rosenberg, M. 2000. The bearing correlogram: a new method of analyzing directional spatial autocorrelation. Geographical Analysis, 32: 267-278.
# NOT RUN { data(eco.test) variog <- eco.variogram(Z = eco[["P"]][, 2],XY = eco[["XY"]]) plot(variog) # variogram plots support the use of ggplot2 syntax require(ggplot2) variogplot <- eco.plotCorrelog(variog) + theme_bw() + theme(legend.position="none") variogplot #----------------------- # ACCESSORS USE EXAMPLE #----------------------- # the slots are accessed with the generic format # (ecoslot. + name of the slot + name of the object). # See help("EcoGenetics accessors") ecoslot.OUT(variog) # slot OUT ecoslot.BREAKS(variog) # slot BREAKS # }