MINDEX_SP {IDmining} | R Documentation |
The Multipoint Morisita Index for Spatial Patterns
Description
Computes the multipoint Morisita index for spatial patterns (i.e. 2-dimensional patterns).
Usage
MINDEX_SP(X, scaleQ=1:5, mMin=2, mMax=5, Wlim_x=NULL, Wlim_y=NULL)
Arguments
X |
A |
scaleQ |
Either a single value or a vector. It contains the value(s) of |
mMin |
The minimum value of |
mMax |
The maximum value of |
Wlim_x |
A vector controlling the spatial extent of the |
Wlim_y |
A vector controlling the spatial extent of the |
Details
-
Q^{(1/2)}
is the number of grid cells (or quadrats) along each of the two axes. -
Q^{(1/2)}
is directly related to\delta
(see References). -
\delta
is the diagonal length of the grid cells.
Value
A data.frame
containing the value of the m-Morisita index for each value of
\delta
and m
.
Author(s)
Jean Golay jeangolay@gmail.com
References
J. Golay, M. Kanevski, C. D. Vega Orozco and M. Leuenberger (2014). The multipoint Morisita index for the analysis of spatial patterns, Physica A 406:191–202.
L. Telesca, J. Golay and M. Kanevski (2015). Morisita-based space-clustering analysis of Swiss seismicity, Physica A 419:40–47.
L. Telesca, M. Lovallo, J. Golay and M. Kanevski (2016). Comparing seismicity declustering techniques by means of the joint use of Allan Factor and Morisita index, Stochastic Environmental Research and Risk Assessment 30(1):77-90.
Examples
sim_dat <- SwissRoll(1000)
m <- 2
scaleQ <- 1:15 # It starts with a grid of 1^2 cell (or quadrat).
# It ends with a grid of 15^2 cells (or quadrats).
mMI <- MINDEX_SP(sim_dat[,c(1,2)], scaleQ, m, 5)
plot(mMI[,1],mMI[,2],pch=19,col="black",xlab="",ylab="")
title(xlab=expression(delta),cex.lab=1.5,line=2.5)
title(ylab=expression(I['2,'*delta]),cex.lab=1.5,line=2.5)
## Not run:
require(colorRamps)
colfunc <- colorRampPalette(c("blue","red"))
color <- colfunc(4)
dev.new(width=5,height=4)
plot(mMI[5:15,1],mMI[5:15,2],pch=19,col=color[1],xlab="",ylab="",
ylim=c(1,max(mMI[,5])))
title(xlab=expression(delta),cex.lab=1.5,line=2.5)
title(ylab=expression(I['2,'*delta]),cex.lab=1.5,line=2.5)
for(i in 3:5){
points(mMI[5:15,1],mMI[5:15,i],pch=19,col=color[i-1])
}
legend.text<-c("m=2","m=3","m=4","m=5")
legend.pch=c(19,19,19,19)
legend.lwd=c(NA,NA,NA,NA)
legend.col=c(color[1],color[2],color[3],color[4])
legend("topright",legend=legend.text,pch=legend.pch,lwd=legend.lwd,
col=legend.col,ncol=1,text.col="black",cex=0.9,box.lwd=1,bg="white")
xlim_l <- c(-5,5) # By default, the spatial extent of the grid is set so
ylim_l <- c(-6,6) # that it is the same as the spatial extent of the data.
xlim_s <- c(-0.6,0.2) # But it can be modified to cover either a larger (l)
ylim_s <- c(-1,0.5) # or a smaller (s) study area (or validity domain).
mMI_l <- MINDEX_SP(sim_dat[,c(1,2)], scaleQ, m, 5, xlim_l, ylim_l)
mMI_s <- MINDEX_SP(sim_dat[,c(1,2)], scaleQ, m, 5, xlim_s, ylim_s)
## End(Not run)