The Properties of Inverse Pareto Distribution and its Application to Extreme Events
In this paper we present some properties of the inverse Pareto distribution (IPD). We compare IPD to gamma distribution, exponential distribution and generalized Pareto distribution (GPD). The data sets over threshold u are analyzed and obtained by the Monte Carlo simulation and the use of Danish fire data. The maximum likelihoode stimation (MLE) is the parameter estimation. The various measurements of model fitting are the Kolmogorov-Smirnov test (KS test), the Anderson-Darling test (AD test), Akaike information criterion (AIC) and Bayesian Information criterion (BIC). We found that the IPD is a good competitor with GPD for the modeling of extreme events.