d <- read.table('inp_RF_M.txt',skip=1) 
vec_q <- sort(d[,1])
nn <- length(vec_q)
vec_lq1<-log(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-Pearson III
my <- mean(vec_lq1)
sy <- sd(vec_lq1)
ry <- mm*sum((vec_lq1-my)^3)/(mm-1)/(mm-2)/sy^3
bb<-4/ry/ry
aa<-sy/sqrt(bb)
cc<-my-aa*bb
# Quantile of tested value in estimated prob.distribution
zp<-(log(xeps)-cc)/aa
# Non-exceedance probability of tested value 
pp  <-pgamma(zp,shape=bb,rate=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
bb
cc
xeps
zp
pp
ueps
peps
eps0