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#' Discrete Powerlaw Object
#'
#' This function allows to create a discrete powerlaw object to analyze.
#' @param x A vector containing the observations.
#' @param summary Logical, whether print a summary with some information concerning data. By default is set to TRUE.
#' @keywords discrete powerlaw
#' @export displo
#' @examples
#' data(moby)
#' x = moby
#' o = displo(x)
displo = function(x, summary = TRUE)
{
o = new.env()
# check data
x = floor(x)
x = x[x>0]
o$x = sort(x)
o$nx = length(x)
o$ux = sort(unique(x))
o$nux = length(o$ux)
o$p = 1 - cdf(o$x)$y
o$xmin = min(x)
o$xmax = max(x)
o$alpha = numeric()
o$sigma = numeric()
o$xmins = NULL
o$alphas = NULL
t = as.data.frame(table(x))
o$freq = t$Freq
o$cumfreq = cumsum(t$Freq)
# fit exponential
o$fitexp = list()
o$fitexp[["rate"]] = 1/mean(o$x)
# fit poisson
o$fitpois = list()
o$fitpois[["lambda"]] = mean(o$x)
# fit lognormal
o$fitlnorm = list()
o$fitlnorm[["meanlog"]] = sum(log(o$x))/o$nx
o$fitlnorm[["sdlog"]] = sqrt(sum((log(o$x) - o$fitlnorm[["meanlog"]])^2)/o$nx)
# print summary
if (summary)
{
cat("\nDiscrete Powerlaw Object",
"\n************************",
"\nn =", o$nx,
"\nn (unique) =", o$nux,
"\nxmin =", o$xmin,
"\nxmax =", o$xmax,
"\nalpha =", o$alpha,
"\n************************"
)
}
return(o)
}
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