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Quantile matching is a strictly monotone transformation that sends the observed response values $\{y_1, . . . , y_n\}$ to the quantiles of a given target distribution. A likelihood based criterion is developed for comparing one target…

Methodology · Statistics 2020-01-14 Peter McCullagh , Micol Federica Tresoldi

Modeling is a challenging topic and using parametric models is an important stage to reach flexible function for modeling. Weibull distribution has two parameters which are shape $\alpha$ and scale $\beta$. In this study, bimodality…

Methodology · Statistics 2020-12-03 Roberto Vila , Mehmet Niyazi Çankaya

This paper develops a polynomial normal transformation model, whereby various non-normal probability distributions can be simulated by the standard normal distribution. Two methods are presented to determine the coefficients of polynomial…

Methodology · Statistics 2015-08-27 Qing Xiao

In this work, we have taken up some distributions, mostly Weibull family, whose quantile functions could not be obtained using the traditional inversion method. We have solved the same quantile functions by using the inversion method only,…

Computation · Statistics 2025-03-26 Subhashree Patra , Subarna Bhattacharjee

The Median Based Unit Weibull is a new 2 parameter unit Weibull distribution defined on the unit interval (0,1). Estimation of the parameters using MLE encountered some problems like large variance. Using generalized method of moments…

Methodology · Statistics 2024-10-30 Iman Mohamed Attia

The selection of a specific statistical distribution is seldom a simple problem. One strategy consists in testing different distributions (normal, lognormal, Weibull, etc.), and selecting the one providing the best fit to the observed data…

Statistics Theory · Mathematics 2019-10-14 Benito Hernández-Bermejo , Albert Sorribas

In reliability and life data analysis, the Weibull distribution is widely used to accommodate more data characteristics by changing the values of the parameters. We frequently observe many zeros or close to zero data points in reliability…

Methodology · Statistics 2022-06-06 Sumangal Bhattacharya , Ishapathik Das , Muralidharan Kunnummal

A generalization of the generalized inverse Weibull distribution so-called transmuted generalized inverse Weibull dis- tribution is proposed and studied. We will use the quadratic rank transmutation map (QRTM) in order to generate a…

Methodology · Statistics 2013-09-16 Faton Merovci , Ibrahim Elbatal , Alaa Ahmed

Regression for count data is widely performed by models such as Poisson, negative binomial (NB) and zero-inflated regression. A challenge often faced by practitioners is the selection of the right model to take into account dispersion,…

Methodology · Statistics 2018-08-02 Hadeel S. Klakattawi , Veronica Vinciotti , Keming Yu

The Sustainable Development Goals (SDGs) of the United Nations consist of 17 general objectives, subdivided into 169 targets to be achieved by 2030. Several SDG indices and indicators require continuous analysis and evaluation, and most of…

Methodology · Statistics 2025-08-26 João Inácio Scrimini , Cleber Bisognin , Renata Rojas Guerra , Fábio M. Bayer

This paper proposes a new approach to estimating the distribution of a response variable conditioned on observing some factors. The proposed approach possesses desirable properties of flexibility, interpretability, tractability and…

Methodology · Statistics 2023-03-16 Cheng Peng , Stanislav Uryasev

Weibull distribution has received a wide range of applications in engineering and science. The utility and usefulness of an estimator is highly subject to the field of practitioner's study. In practice users looking for their desired…

Computation · Statistics 2019-02-18 Sahar Sadani , Kamel Abdollahnezhad , Mahdi Teimouri , Vahid Ranjbar

We define data transformations that leave certain classes of distributions invariant, while acting in a specific manner upon the parameters of the said distributions. It is shown that under such transformations the maximum likelihood…

Statistics Theory · Mathematics 2023-07-10 Muneya Matsui , Simos Meintanis

For the basic maximum likelihood estimating function of the two parameters Weibull distribution, a simple proof on its global monotonicity is given to ensure the existence and uniqueness of its solution. The boundary of the function's…

Methodology · Statistics 2009-10-04 DeTao Mao , Wenyuan Li

We propose a new embedding method, named Quantile-Quantile Embedding (QQE), for distribution transformation and manifold embedding with the ability to choose the embedding distribution. QQE, which uses the concept of quantile-quantile plot…

Machine Learning · Statistics 2021-07-12 Benyamin Ghojogh , Fakhri Karray , Mark Crowley

This paper introduces a new generalization of the power generalized Weibull distribution called the generalized power generalized Weibull distribution. This distribution can also be considered as a generalization of Weibull distribution.…

Statistics Theory · Mathematics 2018-10-16 Mahmoud Ali Selim

We show, in a formal way, how a class of complex quasiprobability distribution functions may be introduced by using the fractional Fourier transform. This leads to the Fresnel transform of a characteristic function instead of the usual…

Quantum Physics · Physics 2019-02-19 Jorge A. Anaya-Contreras , A. Zúñiga-Segundo , Héctor M. Moya-Cessa

For quantum systems with two dimensional configuration space we construct a physical radial momentum observable. Rescaling the radius we find the dilatonic degrees of freedom form a Weyl algebra. With this we construct the radial Wigner…

Quantum Physics · Physics 2008-11-26 J. Twamley

An estimation method is proposed for a wide variety of discrete time stochastic processes that have an intractable likelihood function but are otherwise conveniently specified by an integral transform such as the characteristic function,…

Statistics Theory · Mathematics 2009-09-29 T. Merkouris

The cumulative distribution and quantile functions for the one-sided one sample Kolmogorov-Smirnov probability distributions are used for goodness-of-fit testing. While the Smirnov-Birnbaum-Tingey formula for the CDF appears straight…

Computation · Statistics 2018-02-21 Paul van Mulbregt
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