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lab9R - Areal analysis in R Load Splancs Package Reading...

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Areal analysis in R Load Splancs Package Reading the rushes.dat dataset rushes<-read.table(“rushes.txt”) rushes$x<-rushes[,1] rushes$y<-rushes[,2] plot(as.points(rushes)) poly1<- matrix(c(0,0, 0,1 ,1,1, 1,0),byrow=T, ncol=2) #defines domain EXERCISE 1: Simulating a Homogeneous Poisson process #Function: #csr(poly,npoints) #Arguments: # poly: A polygon data set. # npoints: The number of points to generate. #Details: # 'csr' generates points randomly in the bounding box of 'poly,' #In R: poly1<- matrix(c(0,0, 0,1 ,1,1, 1,0),byrow=T, ncol=2) #defines domain csr(poly1, 100)->csrexample #generates 100 points in the area determined by poly1 plot(csrexample) ##################################################################### EXERCISE 2: POISSON CLUSTER PROCESS # This R code simulates a Poisson cluster process, conditioned on # n=100 points, with 5 parents, h(.) unifrom on a circle of radius .1 # npts <- 100 #no. of offsprings #nparents <- 20 #no. of parents nparents <- 5 #no. of parents #maxrad <- .10 #radius maxrad <- .010 #radius maxdia <- 2*maxrad nkids <- matrix(0,nparents,1) spatpts <- matrix(0,npts,2)
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parxpts <- matrix(runif(nparents),nparents,1) parypts <- matrix(runif(nparents),nparents,1)
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  • Summer '08
  • FUENTES
  • Poisson process, Cardiff, Point process, inhomogeneous poisson process, poisson cluster process, sequential inhibition point

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