# If you donft install sgt package in your R software, firstly please run this R code .
install.packages("sgt", dependencies = TRUE)


#Condition 1-------------------------------------------------------------------
datasetC1 <- c(0.0378*1.05, 0.0378*1.025, 0.0378, 0.0378*0.975, 0.0378*0.95)
datasetC1
logC1 <- log(datasetC1)
logC1
meanC1 <- mean(logC1)
meanC1
varC1 <- var(logC1)
varC1
library(sgt)#package optimx and numDeriv are need to use sgt package 
log(0.0334)
x <- seq(-8, 0, 0.01)
plot(x, dsgt(x, mu=meanC1, sigma = sqrt((1+1/5)*varC1^2), lambda = 0, p=2, q=5/2), type="n")
curve(dsgt(x, mu=meanC1, sigma = sqrt((1+1/5)*varC1^2), lambda = 0, p=2, q=5/2), type="l", add="T")
par(new=T)
px <- c(0, 0, 0, 0, 0)
points(logC1, px)
lower_limit <- log(0.0334)
abline(v=lower_limit)
psgt(lower_limit, mu=meanC1, sigma = sqrt((1+1/5)*varC1^2), lambda = 0, p=2, q=5/2)

#Condition 2-------------------------------------------------------------------
datasetC2 <- c(0.0378*1.5, 0.0378*1.25, 0.0378, 0.0378*0.75, 0.0378*0.5)
datasetC2
logC2 <- log(datasetC2)
logC2
meanC2 <- mean(logC2)
meanC2
varC2 <- var(logC2)
varC2
library(sgt)#package optimx and numDeriv are need to use sgt package 
log(0.0334)
x <- seq(-8, 0, 0.01)
plot(x, dsgt(x, mu=meanC2, sigma = sqrt((1+1/5)*varC2^2), lambda = 0, p=2, q=5/2), type="n")
curve(dsgt(x, mu=meanC2, sigma = sqrt((1+1/5)*varC2^2), lambda = 0, p=2, q=5/2), type="l", add="T")
par(new=T)
px <- c(0, 0, 0, 0, 0)
points(logC2, px)
lower_limit <- log(0.0334)
abline(v=lower_limit)
psgt(lower_limit, mu=meanC2, sigma = sqrt((1+1/5)*varC2^2), lambda = 0, p=2, q=5/2)

#Condition 3-------------------------------------------------------------------
datasetC3 <- c(0.0378*1.64, 0.0378*1.32, 0.0378, 0.0378*0.68, 0.0378*0.36)
datasetC3
logC3 <- log(datasetC3)
logC3
meanC3 <- mean(logC3)
meanC3
varC3 <- var(logC3)
varC3
library(sgt)#package optimx and numDeriv are need to use sgt package 
log(0.0334)
x <- seq(-8, 0, 0.01)
plot(x, dsgt(x, mu=meanC3, sigma = sqrt((1+1/5)*varC3^2), lambda = 0, p=2, q=5/2), type="n")
curve(dsgt(x, mu=meanC3, sigma = sqrt((1+1/5)*varC3^2), lambda = 0, p=2, q=5/2), type="l", add="T")
par(new=T)
px <- c(0, 0, 0, 0, 0)
points(logC3, px)
lower_limit <- log(0.0334)
abline(v=lower_limit)
psgt(lower_limit, mu=meanC3, sigma = sqrt((1+1/5)*varC3^2), lambda = 0, p=2, q=5/2)

#Condition 4-------------------------------------------------------------------
datasetC4 <- c(0.0378*1.82, 0.0378*1.41, 0.0378, 0.0378*0.59, 0.0378*0.18)
datasetC4
logC4 <- log(datasetC4)
logC4
meanC4 <- mean(logC4)
meanC4
varC4 <- var(logC4)
varC4
library(sgt)#package optimx and numDeriv are need to use sgt package 
log(0.0334)
x <- seq(-8, 0, 0.01)
plot(x, dsgt(x, mu=meanC4, sigma = sqrt((1+1/5)*varC4^2), lambda = 0, p=2, q=5/2), type="n")
curve(dsgt(x, mu=meanC4, sigma = sqrt((1+1/5)*varC4^2), lambda = 0, p=2, q=5/2), type="l", add="T")
par(new=T)
px <- c(0, 0, 0, 0, 0)
points(logC4, px)
lower_limit <- log(0.0334)
abline(v=lower_limit)
psgt(lower_limit, mu=meanC4, sigma = sqrt((1+1/5)*varC4^2), lambda = 0, p=2, q=5/2)