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Showing 4 results for Moments
Ali Doostmoradi, Mohammadreza Zadkarami, Mohammadreza Akhoond, Aref Khanjari Idenak, Volume 8, Issue 2 (3-2015)
Abstract
In this paper a new distribution function based on Weibull distribution is introduced. Then the characteristics of this new distribution are considered and a real data set is used to compare this distribution with some of the generalized Weibull distributions.
Farnoosh Ashoori, Malihe Ebrahimpour, Abolghasem Bozorgnia, Volume 9, Issue 2 (2-2016)
Abstract
Distribution of extreme values of a data set is especially used in natural phenomena including flow discharge, wind speeds, precipitation and it is also used in many other applied sciences such as reliability studies and analysis of environmental extreme events. So if one can model the extremal behavior, then the manner of their future behavior can be predicted. This article is devoted to study extreme wind speeds in Zahedan city using maximal generalized extreme value distribution. In this article, we apply four methods to estimate distribution parameters including maximum likelihood estimation, probability weighted moments, elemental percentile and quantile least squares then compare estimates by average scaled absolute error criterion. We also obtain quantiles estimation and confidence intervals. As a part of result, return period of maximum wind speeds are computed.
Ali Doostmoradi, Mohammadreza Zadkarami, Aref Khanjari Idenak, Zahara Fereidooni, Volume 10, Issue 1 (8-2016)
Abstract
In this paper we propose a new distribution based on Weibull distribution. This distribution has three parameters which displays increasing, decreasing, bathtub shaped, unimodal and increasing-decreasing-increasing failure rates. Then consider characteristics of this distribution and a real data set is used to compared proposed distribution whit some of the generalized Weibull distribution.
Mr. Majid Hashempour, Mr. Morteza Mohammadi, Volume 18, Issue 2 (2-2025)
Abstract
This paper introduces the dynamic weighted cumulative residual extropy criterion as a generalization of the weighted cumulative residual extropy criterion. The relationship of the proposed criterion with reliability criteria such as weighted mean residual lifetime, hazard rate function, and second-order conditional moment are studied. Also, characterization properties, upper and lower bounds, inequalities, and stochastic orders based on dynamic weighted cumulative residual extropy and the effect of linear transformation on it will be presented. Then, a non-parametric estimator based on the empirical method for the introduced criterion is given, and its asymptotic properties are studied. Finally, an application of the dynamic weighted cumulative residual extropy in selecting the appropriate data distribution on a real data set is discussed.
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