Nothing
# MLE for the Inverse Gaussian distribution
ig_fit <- function(x){
DNAME <- deparse(substitute(x))
stopifnot(is.numeric(x))
samplerange <- max(x) - min(x)
if (samplerange == 0) stop("all observations are identical")
if (min(x) < 0 ) stop("The dataset contains negative observations. \nAll data must be non-negative real numbers.")
n <- length(x)
mu.hat <- mean(x)
lambda.hat <- n / (sum(1 / x - 1 / mu.hat))
fit <- as.matrix(c(mu.hat, lambda.hat))
colnames(fit) <- c("Inverse Gaussian MLE ")
rownames(fit) <- c("mu", "lambda")
return(fit)
}
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