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Showing 8 results for Moment
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.
Peyman Amiri Domari, Mehrdad Naderi, Ahad Jamalizadeh,
Volume 12, Issue 2 (3-2019)
Abstract
In order to construct the asymmetric models and analyzing data set with asymmetric properties, an useful approach is the weighted model. In this paper, a new class of skew-Laplace distributions is introduced by considering a two-parameter weight function which is appropriate to asymmetric and multimodal data sets. Also, some properties of the new distribution namely skewness and kurtosis coefficients, moment generating function, etc are studied. Finally, The practical utility of the methodology is illustrated through a real data collection.
Bibi Maryam Taheri, Hadi Jabbari, Mohammad Amini,
Volume 16, Issue 1 (9-2022)
Abstract
Paying attention to the copula function in order to model the structure of data dependence has become very common in recent decades. Three methods of estimation, moment method, mixture method, and copula moment, are considered to estimate the dependence parameter of copula function in the presence of outlier data. Although the moment method is an old method, sometimes this method leads to inaccurate estimation. Thus, two other moment-based methods are intended to improve that old method. The simulation study results showed that when we use copula moment and mixture moment for estimating the dependence parameter of copula function in the presence of outlier data, the obtained MSEs are smaller. Also, the copula moment method is the best estimate based on MSE. Finally, the obtained numerical results are used in a practical example.
, Dr Seyed Kamran Ghoreishi,
Volume 18, Issue 1 (8-2024)
Abstract
In this paper, we first introduce semi-parametric heteroscedastic hierarchical models. Then, we define a new version of the empirical likelihood function (Restricted Joint Empirical likelihood) and use it to obtain the shrinkage estimators of the models' parameters in these models. Under different assumptions, a simulation study investigates the better performance of the restricted joint empirical likelihood function in the analysis of semi-parametric heterogeneity hierarchical models. Furthermore, we analyze an actual data set using the RJEL method.
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.
Mr. Mehrdad Norouzi Firooz, Hossein Jabbari Khamnei, Ali Akbar Heydari,
Volume 20, Issue 1 (9-2026)
Abstract
The aim of this paper is to develop statistical inference methods for the Lindley-Weibull distribution when only upper record values are available. Using record theory, likelihood functions for parameter estimation are derived, and maximum likelihood estimators are presented. Additionally, a method for predicting future records based on observed records is proposed. The performance of the methods is evaluated through a simulation study and an application to real flood discharge data. The results indicate that the Lindley-Weibull distribution has high flexibility in modeling record data, and the proposed inference methods have appropriate accuracy.
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