# tests/t-init-actuar.R In fitdistrplus: Help to Fit of a Parametric Distribution to Non-Censored or Censored Data

```if(FALSE)
{

require(fitdistrplus)

#test actuar initialization

start.arg.default <- fitdistrplus:::start.arg.default

#burr
library(actuar)
alpha <- 3
x <- rburr(1000, alpha, 4, .1)

initburr <- function(x)
{
pi <- 1:3/4
qi <- 1-pi
xi <- as.numeric(quantile(x, probs=pi))
y <- log(xi[2])/log(xi[1]/xi[2])
y1 <- log(xi[3]/xi[2])/log(xi[2]/xi[1])
y2 <- log(xi[1]/xi[3])/log(xi[2]/xi[1])
f <- function(eta)
(qi[1]^eta-1)^y1*(qi[2]^eta-1)^y2*(qi[3]^eta-1) - 1
eta <- try(uniroot(f, c(-10, -1e-6))\$root, silent=TRUE)
if(class(eta) == "try-error")
eta <- -1
alpha <- -1/eta
lambda <- (qi[1]^eta-1)^y*(qi[2]^eta-1)^(-y-1)
gamma <- log(lambda*(qi[1]^eta-1))/log(xi[1])
theta <- lambda^(1/gamma)
list(shape1=alpha, shape2=gamma, rate=1/theta)
}

initburr(x)

#fitdist(x, "burr", lower=0, start=initburr(x))

#transformed gamma
x <- rtrgamma(1000, 3, 2, .1)

start1 <- start.arg.default(x, "trgamma")

plot(ecdf(x))
curve(ptrgamma(x, start1\$shape1, start1\$shape2, start1\$rate), add=TRUE, lty=2)

#fitdist(x, "trgamma", lower=0)

#inverse transformed gamma
y <- rinvtrgamma(1000, 3, 2, .1)

start1 <- start.arg.default(y, "invtrgamma")

plot(ecdf(y))
curve(pinvtrgamma(x, start1\$shape1, start1\$shape2, start1\$rate), add=TRUE, lty=2)

#fitdist(y, "invtrgamma")

}
```

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fitdistrplus documentation built on May 2, 2019, 7:24 a.m.