MLE.gpd: Maximum Likelihood estimation of the Generalized Pareto...

In freakonometrics/TopIncome: Estimation of Top Incomes Using Pareto Models

Description

Maximum Likelihood estimation of the Generalized Pareto distribution, with weights

Usage

MLE.gpd(
  data,
  weights = rep(1, length(data)),
  threshold = NA,
  nextremes = NA,
  method = "ml",
  information = c("observed", "expected"),
  ...
)

Arguments

data	a vector of observations
weights	a vector of weights (default = 1)
method	method used for inference ("ml" for maximum likelihood)
information	(not used)
threhold	the threshold parameter of the Generalized Pareto distribution (mu)
nextrmes	the number of largest values considered (integer)

Value

a list xi the tail index, mu the threshold, "beta" the scaling coefficient, and k the number of observations above mu

Examples

set.seed(123)
x <- rpareto1(100, 1, 1.5)
w <- rgamma(100,10,10)
estim <- MLE.gpd(data=x, weights=w, threshold=1)
estim$par.ests

freakonometrics/TopIncome documentation built on Oct. 16, 2021, 5:58 p.m.