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A new family of generalized distributions

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TLDR
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...

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A new method for generating families of continuous distributions

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The Kumaraswamy Weibull distribution with application to failure data

TL;DR: This work introduces and study some mathematical properties of the Kumaraswamy Weibull distribution that is a quite flexible model in analyzing positive data and provides explicit expressions for the moments and moment generating function.
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Generalized Beta-Generated Distributions

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Generalized beta-generated distributions

TL;DR: The generalized beta-generated (GBG) distributions as mentioned in this paper are a subclass of GBG distributions, and they have tractable properties: they can be expanded for moments, generating function and quantiles.
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An extended Lomax distribution

TL;DR: In this article, a new five-parameter continuous distribution, the so-called McDonald Lomax distribution, was proposed and studied, which has as special sub-models new four-and threeparameter distributions, including expansions for the density function, explicit expressions for the moments, generating and quantile functions, mean deviations and Renyi entropy.
References
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Journal ArticleDOI

Estimation of reservoir yield and storage distribution using moments analysis

TL;DR: In this article, the first and second moments of the storage state distribution in terms of the moment of the inflow distribution are derived for specified drafts, using a non-linear solver.
Journal ArticleDOI

Grain yield reliability analysis with crop water demand uncertainty

TL;DR: In this article, a new method of reliability analysis for crop water production function is presented considering crop water demand uncertainty, which uses an advanced first-order second moment (AFOSM) method in evaluating the crop yield failure probability.
Journal ArticleDOI

Maximization of Manufacturing Yield of Systems with Arbitrary Distributions of Component Values

TL;DR: This paper presents a general method for maximizing manufacturing yield when the realizations of system components are independent random variables with arbitrary distributions.
Journal ArticleDOI

Application of double bounded probability density function for analysis of ocean waves

TL;DR: In this article, a double bounded probability density function is used to describe the ocean wave statistics and estimate the most probable maximum wave height for offshore structural designs, where the wave height is defined as the probability that the wave reaches a given height.
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