Moran plots are one of the many way to depict spatial autocorrelation:

moran.test(varofint,listw)

where “varofint” is the variable we are studying, “listw” a listwise neighbourhood matrix, and the function “moran.test” performs the Moran’s test (duh!) for spatial autocorrelation and is included in the spdep funtionality. The same plot can be done using ggplo2 library. Provided that we already have our listwise matrix of neighborhood relationships listw , we first define the variable and the lagged variable under study, computing their mean and saving them into a data frame (there are a lot of datasets you can find implemented in R: afcon, columbus, syracuse, just to cite a few). The purpose is to obtain something that looks like this (I have used my own *large* set of Spanish data to obtain it):

Upload your data. Here is Anselin (1995) data on African conflicts, afcon :

data(afcon)

varofint listw varlag var.name <- "Total Conflicts"

m.varofint m.varlag

and compute the local Moran's statistic using localmoran :



lisa

and save everything into a dataframe:

df

use these variables to derive the four sectors "High-High"(red), "Low-Low"(blue), "Low-High"(lightblue), "High-Low"(pink):

df$sector significance vec =df$m.varofint & df$varlag>=df$m.varlag] df$sector[df$varofint<df$m.varofint & df$varlag<df$m.varlag] df$sector[df$varofint<df$m.varofint & df$varlag>=df$m.varlag] =df$m.varofint & df$varlag<df$m.varlag]



df$sec.data



df$sector.col[df$sec.data==1] <- "red"

df$sector.col[df$sec.data==2] <- "blue"

df$sector.col[df$sec.data==3] <- "lightblue"

df$sector.col[df$sec.data==4] <- "pink"

df$sector.col[df$sec.data==0] <- "white"

df$sizevar df$sizevar 0.1)

df$FILL df$BORDER

to get the ggplot graph:

p 0.05", "High-High", "Low-Low","Low-High","High-Low"))+

scale_x_continuous(name=var.name)+

scale_y_continuous(name=paste("Lagged",var.name))+

theme(axis.line=element_line(color="black"),

axis.title.x=element_text(size=20,face="bold",vjust=0.1),

axis.title.y=element_text(size=20,face="bold",vjust=0.1),

axis.text= element_text(colour=" black", size=20, angle=0,face = "plain"),

plot.margin=unit(c(0,1.5,0.5,2),"lines"),

panel.background=element_rect(fill="white",colour="black"),

panel.grid=element_line(colour="grey"),

axis.text.x = element_text(hjust=.5, vjust=.5),

axis.text.y = element_text(hjust=1, vjust=1),

strip.text.x = element_text(size = 20, colour ="black", angle = 0),

plot.title= element_text(size=20))+

stat_smooth(method="lm",se=F,colour="black", size=1)+

geom_vline(xintercept=m.varofint,colour="black",linetype="longdash")+

geom_hline(yintercept=m.varlag,colour="black",linetype="longdash")+

theme(legend.background =element_rect("white"))+

theme(legend.key=element_rect("white",colour="white"),

legend.text =element_text(size=20))

Check out the interactive shiny version on pracademic