Fitting Power Law Distribution

data <- c(0.35, 0.28, 0.25, 0.21, 0.18, 0.15, 0.13)
data <- data.frame(data)
colnames(data) <- "Retention"

data_num <- as.numeric(data[,1])

fd <- fitdistr(data_num, 'pareto', method = "mle")
summary(fd)


 # http://www.inside-r.org/packages/cran/igraph/docs/power.law.fit

library(igraph)
power.law.fit(data_num,implementation="R.mle")


# https://stats.stackexchange.com/questions/27426/how-do-i-fit-a-set-of-data-to-a-pareto-distribution-in-r

pareto.MLE <- function(X)
{
  n <- length(X)
  m <- min(X)
  a <- n/sum(log(X)-log(m))
  return( c(m,a) ) 
}

pareto.MLE(data_num)