SE distribution
dSE = function(x, p, log = FALSE) #log of pdf of SE model
{
n=count(x)
loglik <- (log(pi/2)+log(p)-(p*x)+log(sin((pi/2)*exp(-x*p))))
if ( log == FALSE)
density <- exp(loglik)
else density <- loglik
return(density)
}
theta <- maxlogL(x =st, dist = "dSE",start = 0.59)
summary(theta)
#IL distribution
dIL = function(x,p, log = FALSE)
{
n=count(x)
loglik <- (2*log(p))-log(1+p)-(p/x)+log(1+x)-(3*log(x))
if ( log == FALSE)
density <- exp(loglik)
else density <- loglik
return(density)
}
theta <- maxlogL(x =st, dist = "dIL",start = 0.65)
summary(theta)
```

```
#Exp distribution
dE = function(x,p, log = FALSE) #log of pdf of Expo model
{
n=count(x)
loglik <- log(dexp(x, p, log = FALSE))
if ( log == FALSE)
density <- exp(loglik)
else density <- loglik
return(density)
}
st = c(2.15, 2.20, 2.55, 2.56, 2.63, 2.74, 2.81, 2.90, 3.05, 3.41, 3.43,
 3.43, 3.84, 4.16, 4.18, 4.36, 4.42, 4.51, 4.60, 4.61, 4.75, 5.03, 5.10,
 5.44, 5.90, 5.96, 6.77, 7.82, 8.00, 8.16, 8.21, 8.72, 10.40, 13.20, 13.70)
theta <- maxlogL(x =st, dist = "dE",start = 0.6)
summary(theta)
Appendix A.4. KS Test Statistic, p-Value and Other Test Statistics
install.packages ("goftest")
library(goftest)
y = c(2.15, 2.20, 2.55, 2.56, 2.63, 2.74, 2.81, 2.90, 3.05, 3.41, 3.43,
 3.43, 3.84, 4.16, 4.18, 4.36, 4.42, 4.51, 4.60, 4.61, 4.75, 5.03, 5.10,
 5.44, 5.90, 5.96, 6.77, 7.82, 8.00, 8.16, 8.21, 8.72, 10.40, 13.20, 13.70)