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In this paper a new lifetime distribution which is obtained by compounding Lindley and geometric distributions, named Lindley-geometric (LG) distribution, is introduced. Several properties of the new distribution such as density, failure…

Computation · Statistics 2012-04-20 Hojjatollah Zakerzadeh , Eisa Mahmoudi

In this article, the exponentiated discrete Lindley distribution is presented and studied. Some important distributional properties are discussed. Using the maximum likelihood method, estimation of the model parameters is investigated.…

Statistics Theory · Mathematics 2018-07-27 M. El-Morshedy , M. S. Eliwa , H. Nagy

To know the statistical distribution of a variable is an important problem in management of resources. Distributions of the power law type are observed in many real systems. However power law distributions have an infinite variance and thus…

Statistical Mechanics · Physics 2008-12-02 Hari M. Gupta , Jose R. Campanha

Targeted maximum likelihood estimation (TMLE) is a general method for estimating parameters in semiparametric and nonparametric models. Each iteration of TMLE involves fitting a parametric submodel that targets the parameter of interest. We…

Methodology · Statistics 2014-06-03 Iván Díaz , Michael Rosenblum

In this paper, we introduce a new probability distribution, the Lasso distribution. We derive several fundamental properties of the distribution, including closed-form expressions for its moments and moment-generating function.…

This article aims to introduced a new lifetime distribution named as exponentiated xgamma distribution (EXGD). The new generalization obtained from xgamma distribution, a special finite mixture of exponential and gamma distributions. The…

Statistics Theory · Mathematics 2018-10-22 Abhimanyu Singh Yadav , Mahendra Saha , Harsh Tripathi , Sumit Kumar

In this paper, a new mixed Poisson distribution is introduced. This new distribution is obtained by utilizing mixing process, with Poisson distribution as mixed distribution and Transmuted Exponential distribution as mixing distribution.…

Methodology · Statistics 2016-10-05 Deepesh Bhati , Pooja Kumawat , E. Gómez Déniz

The family of q-Gaussian and q-exponential probability densities fit the statistical behavior of diverse complex self-similar non-equilibrium systems. These distributions, independently of the underlying dynamics, can rigorously be obtained…

Statistical Mechanics · Physics 2015-05-19 Adrian A. Budini

Several generalizations of the logistic distribution, and certain related models, are proposed by many authors for modeling various random phenomena such as those encountered in data engineering, pattern recognition, and reliability…

Statistics Theory · Mathematics 2019-03-19 Seema S Nair , Nicy Sebastian

In this paper, we introduce a new two-parameter lifetime distribution, called the exponential-generalized truncated logarithmic (EGTL) distribution, by compounding the exponential and generalized truncated logarithmic distributions. Our…

Statistics Theory · Mathematics 2018-09-28 Mohieddine Rahmouni , Ayman Orabi

In numerous instances, the generalized exponential distribution can be used as an alternative to the most widely used non-regular family of distributions: Weibull, gamma, lognormal with three-parameters when analyzing lifetime or any skewed…

Methodology · Statistics 2026-03-03 Kiran Prajapat , Sharmishtha Mitra , Debasis Kundu

Lately, a New Transmuted Logistic-exponential (NTLE) distribution was introduced and studied as an extension of the Logistic-Exponential Distribution (LED) with wider applicability in lifetime modelling. However, the maximum likelihood…

Using a coupled parametric-resonator array for generating and propagating a topological soliton in its rotating-frame phase space is theoretically and numerically investigated. In an analogy with the well-known phi4 model, the existence of…

Pattern Formation and Solitons · Physics 2021-04-07 Hiroshi Yamaguchi , Samer Houri

This paper presents a new methodology for generating continuous statistical distributions, integrating the exponentiated odds ratio within the framework of survival analysis. This new method enhances the flexibility and adaptability of…

Statistics Theory · Mathematics 2024-02-28 Xinyu Chen , Yuanqi Xie , Achraf Cohen , Shusen Pu

In this paper, we propose Continuous Graph Flow, a generative continuous flow based method that aims to model complex distributions of graph-structured data. Once learned, the model can be applied to an arbitrary graph, defining a…

Machine Learning · Computer Science 2019-10-01 Zhiwei Deng , Megha Nawhal , Lili Meng , Greg Mori

Copulas, generalized estimating equations, and generalized linear mixed models promote the analysis of grouped data where non-normal responses are correlated. Unfortunately, parameter estimation remains challenging in these three…

Methodology · Statistics 2024-10-16 Sarah S. Ji , Benjamin B. Chu , Hua Zhou , Kenneth Lange

In this paper, we proposed a new lifetime distribution namely generalized weighted Lindley (GLW) distribution. The GLW distribution is a useful generalization of the weighted Lindley distribution, which accommodates increasing, decreasing,…

Statistics Theory · Mathematics 2016-07-20 P. L. Ramos , F. Louzada

In this paper we propose a new four-parameters distribution with increasing, decreasing, bathtub-shaped and unimodal failure rate, called as the exponentiated Weibull-Poisson (EWP) distribution. The new distribution arises on a latent…

Methodology · Statistics 2012-12-24 Eisa Mahmoudi , Afsaneh Sepahdar

We introduce and study a class of probabilistic generative models, where the latent object is a finite-dimensional diffusion process on a finite time interval and the observed variable is drawn conditionally on the terminal point of the…

Probability · Mathematics 2019-06-03 Belinda Tzen , Maxim Raginsky

We use the configuration model to generate networks having a degree distribution that follows a $q$-exponential, $P_q(k)=(2-q)\lambda[1-(1-q)\lambda k]^{1/(q-1)}$, for arbitrary values of the parameters $q$ and $\lambda$. We study the…