moran.scatterplot: Moran Scatter Plot

In spdyn: Exploratory Space-Time Data Analysis

Moran Scatter Plot

Description

This function produces the moran scatterplot.

Usage

moran.scatterplot(x,y,listw,CENT=mean,DESV=sd, lisa, signif, ...)

Arguments

x	A numeric vector.
y	A numeric vector. This is the variable to be spatially lagged. If x is a numeric matrix, there is no need to supply this argument. If x is a column vector and y is not provided, then the univariate moran scatter plot is produced.
listw	A list of spatial weights as provided by spdep::nb2listw
CENT	Central tendency statistic used to compute the Moran Statistic. Defaults to mean
DESV	Dispersion statistic. Defaults to sd
lisa	If an object of class lisaPerm is provided as produced by lisa.perm or by bilisa.perm, then the observations (points) in the moran scatterplot which belong to a significatant cluster are coloured as in the LISA cluster map (ie., red for observations belonging to the High-High cluster, blue for observations in the Low-Low cluster, and so on). However, observations with a non-significant value of the LISAs are coloured in grey30. See signif argument.
signif	If an object of class lisaPerm is provided to the lisa argument, then the signif argument determines the significance threshold to determina significance of LISA statistics.

.

...	Further arguments provided to plot

Details

The moran scatterplot provides a way to visually inspect if there is spatial autocorrelation.

Author(s)

Osmar Leandro Loaiza Quintero

See Also

unimoran, unimoran.test, bimoran, bimoran.test

Examples

data(usinc)

require(spdep)

lw<-nb2listw(
		poly2nb(usinc,queen=TRUE),style='W'
	)

moran.scatterplot(x=usinc$X2007, y=usinc$X2009, listw=lw)

spdyn documentation built on Oct. 28, 2024, 3 p.m.