EcoGenetics (version 1.2.1-4)

eco.variogram: Empirical variogram

Description

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.

Usage

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)

Arguments

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 geoXY.

angle

Direction for computation of a bearing variogram (angle between 0 and 180). Default NULL (omnidirectional).

Value

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

References

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.

Examples

Run this code
# NOT RUN {
data(eco.test)
variog <- eco.variogram(Z = eco[["P"]][, 2],XY =  eco[["XY"]])
eco.plotCorrelog(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

# }
# NOT RUN {
# }

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