Nothing
IndNHNeyScot <-
function(lambdaParent, d,lambdaNumP=1, dist='normal',sigmaC=1, minC=-1,
maxC=1, dplot=TRUE, fixed.seed=NULL,...)
{
#This function generates independent trajectories based on a Neyman-Scott model
#with number of sons Poisson ( with different means to obtain different number of points
#If d=1 a univariate Neyman-Scott process is generated
if (length(lambdaNumP)==1) lambdaNumP<-rep(lambdaNumP,d)
if (length(sigmaC)==1) sigmaC<-rep(sigmaC,d)
if (length(maxC)==1) maxC<-rep(maxC,d)
if (length(minC)==1) minC<-rep(minC,d)
if ( ( (length(lambdaNumP)==d)*(length(sigmaC)==d)*(length(minC)==d)*(length(maxC))==d ) ==0)
stop('The lenght of the arguments lambdaNumP, sigmaC, minC and maxC must be 1 or d')
T<-length(lambdaParent)
posNH<-NULL #list(N1=NULL)
if (!is.null(fixed.seed))
{for (i in c(1:d))
{
posParent<-simNHPc(lambda=lambdaParent, fixed.seed=(fixed.seed+i))$posNH
posNH[[i]]<-GenSons(posParent, lambdaNumP=lambdaNumP[i], dist=dist, sigmaC=sigmaC[i],
minC=minC[i],maxC=maxC[i], Tf=T,fixed.seed=(fixed.seed+i))$pos
}
} else
{for (i in c(1:d))
{
posParent<-simNHPc(lambda=lambdaParent)$posNH
posNH[[i]]<-GenSons(posParent, lambdaNumP=lambdaNumP[i], dist=dist, sigmaC=sigmaC[i],
minC=minC[i],maxC=maxC[i], Tf=T)$pos
}
}
names(posNH)<-paste('N',c(1:d), sep='')
if (dplot==TRUE) PlotMargP(listpos=posNH,T=T,...)
return(posNH)
}
Any scripts or data that you put into this service are public.
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.