PrintQuadrat Analysis in R
Like nearest neighbor distance analysis, quadrat analysis is a relatively limited method for the analysis of a point pattern, as has been discussed in the text. However, it is easy to perform in R, and can provide useful insight into the distribution of events in a pattern.
The functions you need in spatstat are quadratcount() and quadrat.test():
1 2 | > q <- quadratcount(xhomicide, 4, 8) > quadrat.test(xhomicide, 4, 8) |
The second and third parameters supplied to these functions are the number of quadrats to create across the study area in the x (east-west) and y (north-south) directions. The test will report a p-value, which can be used to determine whether the pattern is statistically different from one generated by IRP/CSR.
1 2 3 4 5 6 7 8 9 10 | #Quadrat Analysis q <-quadratcount(xhomicide, 4, 8) plot(q) #Add intensity of each quadrat#Note, depending on your version of R, this line of code may not work correctly plot(intensity(q, image=TRUE), main=NULL, las=1) #perform the significance test quadrat.test(xhomicide, 4, 8) |
Repeat this for the other crimes that you selected to analyze.