test=matrix(scan("Leesferry-mon-data.txt"), ncol=13, byrow=T)

sepflow = test[,9]*0.0004690502
x=sepflow

library(Rlab)
ncls = round(log(95,2)+1)

# create the grid.. 
N=250
lbound = 0	#lowerbound
xx1=seq(max(lbound,min(x)-sd(x)),max(x)+sd(x),length=N)

#histogram and overlay PDF
hplot(sepflow,nclass=ncls,probability=T,xlim=range(xx1),xlab="Sep flow",ylab="PDF")
 lines(xx1,dlnorm(xx1,meanlog=mean(log(x)), sdlog=sd(log(x))), col="red")

source("qgaus.r")
source("integrand-lnormal.r")

N1=N-1
zz=1:N1
 for(i in 2:N){
x1=xx1[i-1]
 x2=xx1[i]
 zz[i-1]=qgaus(x1,x2,x)}
zz=cumsum(zz)

plot(xx1[1:N1],zz,type="l",xlab="Sep flow", ylab="CDF")