SphericalK (version 1.2)

sphere_montekhat: K-functions Under Complete Spatial Randomness (CSR) By Monte Carlo Tests

Description

Monte Carlo confidence intervals of K-functions under CSR are provided for point-pattern analysis.

Usage

sphere_montekhat(n, nsim, dis)

Arguments

n

Number of observed points

nsim

Number of simulations for K-function

dis

Vector of values for the argument r (from 0 to pi), at which K(r) is evaluated. By default, dis = seq(from=0,to=pi,by=0.1).

Value

Kci Simulated K-functions under CSR

References

Robeson, S.M., Li, A., Huang, C., 2014. Point-pattern analysis on the sphere. Spatial Statistics. 10, 76-86.

See Also

sphere_khat, GUAN

Examples

#Spherical K function (minus CSR) with 95% confidence intervals
#for point patterns associated with 172 upper-air monitoring stations points

data(GUAN)
latg<-GUAN[,4]
long<-GUAN[,5]
d<-seq(from=0,to=pi,by=0.1)
nd<-length(d)
d[nd]<-pi
khatsg<-sphere_khat(latg,long,d)
Kcig<-sphere_montekhat(172,16,d)
plot(d,khatsg,type='n', ylim=c(-0.1,0.15),xlim=c(0,pi),xaxt = "n",
     ylab = expression(K - CSR),xlab = expression("Spherical Angle"))
axis(1, at = c(0,pi/6, pi/3, pi/2, 2*pi/3, 5*pi/6, pi),
     labels = expression(0,pi/6, pi/3, pi/2, 2*pi/3, 5*pi/6, pi))
polygon(c(d, rev(d)), c(Kcig[2,], rev(Kcig[16,])),col = "grey79", border = FALSE)
lines(d,khatsg,col = 4, lwd=2)
lines(y=c(0,0),x=c(0,pi),type='l',lty=2,lwd=2)