Journal ArticleDOI
A new family of generalized distributions
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In this paper, a new family of generalized distributions for double-bounded random processes with hydrological applications is described, including Kw-normal, Kw-Weibull and Kw-Gamma distributions.Abstract:
Kumaraswamy [Generalized probability density-function for double-bounded random-processes, J. Hydrol. 462 (1980), pp. 79–88] introduced a distribution for double-bounded random processes with hydrological applications. For the first time, based on this distribution, we describe a new family of generalized distributions (denoted with the prefix ‘Kw’) to extend the normal, Weibull, gamma, Gumbel, inverse Gaussian distributions, among several well-known distributions. Some special distributions in the new family such as the Kw-normal, Kw-Weibull, Kw-gamma, Kw-Gumbel and Kw-inverse Gaussian distribution are discussed. We express the ordinary moments of any Kw generalized distribution as linear functions of probability weighted moments (PWMs) of the parent distribution. We also obtain the ordinary moments of order statistics as functions of PWMs of the baseline distribution. We use the method of maximum likelihood to fit the distributions in the new class and illustrate the potentiality of the new model with a...read more
Citations
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Journal ArticleDOI
Inference for a Kavya–Manoharan Inverse Length Biased Exponential Distribution under Progressive-Stress Model Based on Progressive Type-II Censoring
Naif khaled alotaibi,Atef F. Hashem,Ibrahim Elbatal,Salem A. Alyami,A. S. Al-Moisheer,Mohammed Elgarhy +5 more
TL;DR: In this paper , a new one parameter survival model is proposed using the Kavya-Manoharan (KM) transformation family and the inverse length biased exponential (ILBE) distribution.
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Beta Kumaraswamy Burr Type X Distribution and Its Properties
Abstract: We proposed a so-called Beta Kumaraswamy Burr Type X distribution which gives the extension of the Kumaraswamy-G class of family distribution. Some properties of this proposed model were provided, like: the expansion of densities and quantile function. We considered the Bayes and maximum likelihood methods to estimate the parameters and also simulate the model parameters to validate the methods based on different set of true values. Some real data sets were employed to show the usefulness and flexibility of the model which serves as generalization to many sub-models in the field of engineering, medical, survival and reliability analysis.
Journal ArticleDOI
The Kumaraswamy skew-t distribution and its related properties
TL;DR: This article introduces a new generalization of the skew-t distribution based on the Kumaraswamy generalized distribution, which has the ability of fitting skewed, long, and heavy-tailed data and is more flexible than the skewness distribution as it contains the skew -t distribution as a special case.
Journal ArticleDOI
The Modified Burr III G family of Distributions
TL;DR: The Modified Burr III G family as discussed by the authors is a family of distributions based on a generalized Burr III generator, and its density function can be Bell-shaped, left-skewed, right-sided, bathtub, inverted-down, or reversed-J. Some of its special models are presented.
Journal ArticleDOI
The Generalized Weibull-Burr Xii Distribution and Its Applications
Najmieh Maksaei,Emrah Altun +1 more
TL;DR: In this article, a new lifetime model, called the Generalized Weibull-Burr XII distribution, was introduced, and a simulation study is performed to assess the performance of maximum likelihood estimators by means of biases, mean squared errors.
References
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Journal ArticleDOI
Statistical Theory of Reliability and Life Testing Probability Models
Book
Statistical Theory of Reliability and Life Testing: Probability Models
Richard E. Barlow,Frank Proschan +1 more
TL;DR: A number of new classes of life distributions arising naturally in reliability models are treated systematically and each provides a realistic probabilistic description of a physical property occurring in the reliability context, thus permitting more realistic modeling of commonly occurring reliability situations.
Journal ArticleDOI
L-Moments: Analysis and Estimation of Distributions Using Linear Combinations of Order Statistics
TL;DR: The authors define L-moments as the expectations of certain linear combinations of order statistics, which can be defined for any random variable whose mean exists and form the basis of a general theory which covers the summarization and description of theoretical probability distributions.
Journal Article
A class of distributions which includes the normal ones
TL;DR: In this paper, a nouvelle classe de fonctions de densite dependant du parametre de forme λ, telles que λ=0 corresponde a la densite normale standard.
Journal ArticleDOI
Generalized additive models for location, scale and shape
TL;DR: The generalized additive model for location, scale and shape (GAMLSS) as mentioned in this paper is a general class of statistical models for a univariate response variable, which assumes independent observations of the response variable y given the parameters, the explanatory variables and the values of the random effects.
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