DutilleulPlot.fun: Performs a Diggle's randomization testing procedure to check...

Description Usage Arguments Details Value References See Also Examples

View source: R/DutilleulPlot.fun.R

Description

This function applies the Diggle's randomization testing procedure extended by Dutilleul(2011) and performs a plot which checks graphically the independence of two point proceses. It is implemented for homogenous and non homogenous processes.

Usage

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DutilleulPlot.fun(posx, posy, lambday, nsim = 1000, lenve = c(0.025, 0.975), ...)

Arguments

posx

Numeric vector. Position of the occurrence points of the first point process.

posy

Numeric vector. Position of the occurrence points of the second point process.

lambday

Numeric vector. Intensity values of the second point process

nsim

Optional. Positive integer. Number of simulations performed to obtain the confidence bands.

lenve

Optional. Numeric vector. Lower and the upper percentiles which determine the limits of the confidence band.

...

Further arguments to be passed to plot.

Details

This is a procedure to check graphically the independence of two point proceses. It is based on the comparison of the cumulative relative frequency of the nearest neighbour distances between the points in the two observed processes, with their counterpart in two independent processes with the same intensities. The procedure consists on plotting the cumulative relative frequency of the observed processes and a confidence band calculated from nsim simulated independent processes.

Value

A list with the elements used in the plot

quantobs

Vector of observed percentiles of the nearest neighbour distances.

enve1

Vector of lower limits of the confidence band.

enve2

Vector of upper limits of the confidence band.

References

Dutilleul, P. (2011), Spatio-temporal heterogeneity: Concepts and analyses, Cambridge University Press.

See Also

TestIndNH.fun, CondTest.fun,nearestdist.fun

Examples

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#Two independent NHPPs
set.seed(123)
lambdax<-runif(200, 0.01,0.1)
set.seed(124)
lambday<-runif(200, 0.015,0.15)
posx<-simNHPc.fun(lambdax,fixed.seed=123)$posNH
posy<-simNHPc.fun(lambday, fixed.seed=123)$posNH

aux<-DutilleulPlot.fun(posx, posy, lambday,  nsim = 100)


#Two dependent NSPs
#set.seed(123)
#lambdaParent<-runif(200)/10
#DepPro<-DepNHNeyScot.fun(lambdaParent=lambdaParent, d=2, lambdaNumP = 3, 
#	dist = "normal", sigmaC = 3,fixed.seed=123)
#posx<-DepPro$PP1
#posy<-DepPro$PP2
#aux<-DutilleulPlot.fun(posx, posy, lambday, nsim = 100)

IndTestPP documentation built on May 29, 2017, 5:19 p.m.