A New Method for Generating Distributions: An Application to Flow Data

Abstract

Nowadays, one of the aim of statistical studies is to provide the future with the models which are easily accessible and simple. Therefore, more suitable distributions are needed to model the data. In this study, a new distribution is generated with exponential marginals Farlie-Gumbel-Morgenstern distribution. Specifications and characteristics of this new distribution are studied. The structure of the proposed distribution is discussed statistically and the parameter estimation for the new distribution is made by known methods. In addition, reliability analysis has performed. Due to the shape and flexibility of the proposed distribution, it is thought to be an alternative to distributions which are used for modeling flow data. Efficiency on the statistical modeling of the new distribution can be detected by using flow data sets in literature. Furthermore, Terme and Sefaatli Creeks' flow-data obtained from Turkish State Water Affairs Directorate are used to model. It is concluded that this new distribution offers a model that can be used effectively in stream flows.