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


#Condition 1-------------------------------------------------------------------
datasetB1 <- c(0.0268*1.05, 0.0268*1.025, 0.0268, 0.0268*0.975, 0.0268*0.95)
datasetB1
logB1 <- log(datasetB1)
logB1
meanB1 <- mean(logB1)
meanB1
varB1 <- var(logB1)
varB1
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=meanB1, sigma = sqrt((1+1/5)*varB1^2), lambda = 0, p=2, q=5/2), type="n")
curve(dsgt(x, mu=meanB1, sigma = sqrt((1+1/5)*varB1^2), lambda = 0, p=2, q=5/2), type="l", add="T")
par(new=T)
px <- c(0, 0, 0, 0, 0)
points(logB1, px)
lower_limit <- log(0.0334)
abline(v=lower_limit)
psgt(lower_limit, mu=meanB1, sigma = sqrt((1+1/5)*varB1^2), lambda = 0, p=2, q=5/2)

#Condition 2-------------------------------------------------------------------
datasetB2 <- c(0.0268*1.5, 0.0268*1.25, 0.0268, 0.0268*0.75, 0.0268*0.5)
datasetB2
logB2 <- log(datasetB2)
logB2
meanB2 <- mean(logB2)
meanB2
varB2 <- var(logB2)
varB2
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=meanB2, sigma = sqrt((1+1/5)*varB2^2), lambda = 0, p=2, q=5/2), type="n")
curve(dsgt(x, mu=meanB2, sigma = sqrt((1+1/5)*varB2^2), lambda = 0, p=2, q=5/2), type="l", add="T")
par(new=T)
px <- c(0, 0, 0, 0, 0)
points(logB2, px)
lower_limit <- log(0.0334)
abline(v=lower_limit)
psgt(lower_limit, mu=meanB2, sigma = sqrt((1+1/5)*varB2^2), lambda = 0, p=2, q=5/2)

#Condition 3-------------------------------------------------------------------
datasetB3 <- c(0.0268*1.64, 0.0268*1.32, 0.0268, 0.0268*0.68, 0.0268*0.36)
datasetB3
logB3 <- log(datasetB3)
logB3
meanB3 <- mean(logB3)
meanB3
varB3 <- var(logB3)
varB3
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=meanB3, sigma = sqrt((1+1/5)*varB3^2), lambda = 0, p=2, q=5/2), type="n")
curve(dsgt(x, mu=meanB3, sigma = sqrt((1+1/5)*varB3^2), lambda = 0, p=2, q=5/2), type="l", add="T")
par(new=T)
px <- c(0, 0, 0, 0, 0)
points(logB3, px)
lower_limit <- log(0.0334)
abline(v=lower_limit)
psgt(lower_limit, mu=meanB3, sigma = sqrt((1+1/5)*varB3^2), lambda = 0, p=2, q=5/2)

#Condition 4-------------------------------------------------------------------
datasetB4 <- c(0.0268*1.82, 0.0268*1.41, 0.0268, 0.0268*0.59, 0.0268*0.18)
datasetB4
logB4 <- log(datasetB4)
logB4
meanB4 <- mean(logB4)
meanB4
varB4 <- var(logB4)
varB4
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=meanB4, sigma = sqrt((1+1/5)*varB4^2), lambda = 0, p=2, q=5/2), type="n")
curve(dsgt(x, mu=meanB4, sigma = sqrt((1+1/5)*varB4^2), lambda = 0, p=2, q=5/2), type="l", add="T")
par(new=T)
px <- c(0, 0, 0, 0, 0)
points(logB4, px)
lower_limit <- log(0.0334)
abline(v=lower_limit)
psgt(lower_limit, mu=meanB4, sigma = sqrt((1+1/5)*varB4^2), lambda = 0, p=2, q=5/2)