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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Three mixed-effects regression models using an extended Weibull with applications on games in differential and integral calculus
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TL;DR: In this paper , three mixed-effects regressions models using an extended Weibull distribution are defined for repeated measures, and their parameters are estimated by maximum likelihood, and Monte Carlo simulations report the accuracy of the maximum likelihood estimators and the distribution of the quantile residuals in these regressions.
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The Generalized Odd Log-Logistic Fréchet Distribution for Modeling Extreme Values
TL;DR: In this paper , a new extension of the Fréchet distribution for modeling the extreme values is introduced, which generalizes eleven distributions at least, and some of them are quite new.
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A New Family of Distributions to Encounter the Extrapolating Issues
TL;DR: In this article , a truncated random variable is used to transform another random variable, which yields a new family of truncated distributions by introducing a new generator, which are equally useful in engineering and biological sciences.
Journal ArticleDOI
A New Five Parameter Lifetime Distribution: Properties and Application
TL;DR: In this article, a new generalization of the Weibull distribution is proposed, called exponentiated exponentiated exponential-Weibull (EEE-W) distribution, which can provide a better fit than some other known distributions.
Journal ArticleDOI
A New Inverse Kumaraswamy Family of Distributions: Properties and Application
TL;DR: In this paper , a new family of inverse Kumaraswamy distributions is introduced and its statistical properties are explored, and a particular sub-model of this family is considered and some properties of the proposed distribution are obtained.
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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