d <- read.table('inp_RF_S.txt',skip=1) 
vec_q <- sort(d[,1])
nn <- length(vec_q)
vec_q1<-vec_q[1:nn-1]
xeps<-vec_q[nn] # Tested value (the maximum value)
mm<-nn-1

# Parameter estimation using sample size of mm=nn-1
# (except the tested value)
# Type of distribution: Log-Normal (Iwai method)
aa <- (vec_q1[1]*vec_q1[mm]-median(vec_q1)^2)/(vec_q1[1]+vec_q1[mm]-2*median(vec_q1))
vec_y <- log(vec_q1-aa)
my <- mean(vec_y)
sy <- sd(vec_y)*sqrt((mm-1)/mm)
# Quantile of tested value in estimated prob.distribution
zp<-(log(xeps-aa)-my)/sy
# Non-exceedance probability of tested value 
pp  <-pnorm(zp,0,1,lower.tail=TRUE,log.p=FALSE)

# Quantile of tested value in Standard Normal distribution
ueps<-qnorm(pp,0,1,lower.tail=TRUE,log.p=FALSE)
# Non-exceedance pprobability in F-distribution
peps<-pf((mm-1)/(mm+1)*ueps^2,1,mm-1,lower.tail=TRUE,log.p=FALSE)
peps<-(1-peps)/2

# Critical level for the significant lebel b0
b0<-0.05
eps0<-1-(1-b0)^(1/nn)

# In the case of peps<=eps0, tested value is rejected.
nn
mm
aa
my
sy
xeps
zp
pp
ueps
peps
eps0