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This paper studies various distributional properties of the Rosenblatt distribution. We begin by describing a technique for computing the cumulants. We then study the expansion of the Rosenblatt distribution in terms of shifted chi-squared…

Statistics Theory · Mathematics 2013-07-24 Mark S. Veillette , Murad S. Taqqu

This paper explores the extension of the classical two-parameter Weibull distribution to a four-parameter Harris extended Weibull (HEW) distribution. The flexibility of this probability distribution is illustrated by the varying shapes of…

Methodology · Statistics 2025-10-01 Prithul Chaturvedi , Himanshu Pokhriyal

The generalized Marshall-Olkin Lomax distribution is introduced, and its properties are easily obtained from those of the Lomax distribution. A regression model for censored data is proposed. The parameters are estimated through maximum…

Statistics Theory · Mathematics 2025-10-16 Alexsandro A. Ferreira , Gauss M. Cordeiro

A multiplicative stochastic process with the lower bound lognormally distributed is investigated. For the process, the model is constructed, and its distribution function (involving four parameters) and the related statistical properties…

Data Analysis, Statistics and Probability · Physics 2024-01-19 Ken Yamamoto , Yoshihiro Yamazaki

The Extended Generalized Pareto Distribution (EGPD) (Naveau et al. 2016) is a family of distribution that has been introduced to model the full range of a positive random variable but with the lower and the upper tails distributed according…

Methodology · Statistics 2022-09-13 Noémie Le Carrer , Carlo Gaetan

We introduce a new approach to a linear-circular regression problem that relates multiple linear predictors to a circular response. We follow a modeling approach of a wrapped normal distribution that describes angular variables and angular…

Methodology · Statistics 2019-09-17 Ali Esmaieeli Sikaroudi , Chiwoo Park

An extension of the regularized least-squares in which the estimation parameters are stretchable is introduced and studied in this paper. The solution of this ridge regression with stretchable parameters is given in primal and dual spaces…

Machine Learning · Computer Science 2018-06-12 Kar-Ann Toh , Lei Sun , Zhiping Lin

The spread of diseases has been studied for many years, but it receives a particular focus recently due to the outbreak and spread of COVID-19. Studies show that the spread of COVID-19 can be characterized by the…

Machine Learning · Computer Science 2022-04-12 Xiaoxu Zhong , Yukun Ye

This article presents a new class of generalized transmuted lifetime distributions which includes a large number of lifetime distributions as sub-family. Several important mathematical quantities such as density function, distribution…

Methodology · Statistics 2024-05-21 Alok Kumar Pandey , Alam Ali , Ashok Kumar Pathak

The main purpose of this paper is to introduce a new class of regression models for bounded continuous data, commonly encountered in applied research. The models, named the power logit regression models, assume that the response variable…

Methodology · Statistics 2026-05-15 Francisco Felipe Queiroz , Silvia Lopes Paula Ferrari

The bivariate Gaussian distribution has been a key model for many developments in statistics. However, many real-world phenomena generate data that follow asymmetric distributions, and consequently bivariate normal model is inappropriate in…

Methodology · Statistics 2022-12-08 Roberto Vila , Narayanaswamy Balakrishnan , Helton Saulo , Ana Protazio

In this work, we explore the theoretical properties of conditional deep generative models under the statistical framework of distribution regression where the response variable lies in a high-dimensional ambient space but concentrates…

Statistics Theory · Mathematics 2026-02-02 Shivam Kumar , Yun Yang , Lizhen Lin

Probabilistic regression models the entire predictive distribution of a response variable, offering richer insights than classical point estimates and directly allowing for uncertainty quantification. While diffusion-based generative models…

Machine Learning · Computer Science 2025-10-07 Carlo Kneissl , Christopher Bülte , Philipp Scholl , Gitta Kutyniok

Distribution regression seeks to estimate the conditional distribution of a multivariate response given a continuous covariate. This approach offers a more complete characterization of dependence than traditional regression methods.…

Statistics Theory · Mathematics 2025-06-10 Rong Tang , Yun Yang

We fit the exponent of the Pareto distribution, that is equivalent or can approximate the continuous power law distribution given a cutoff point, using linear regression (LR). We use LR on the logged variables of the empirical tail (one…

Applications · Statistics 2023-12-21 Samuel Forbes

We consider a log-linear model for survival data, where both the location and scale parameters depend on covariates and the baseline hazard function is completely unspecified. This model provides the flexibility needed to capture many…

Methodology · Statistics 2019-01-16 Kevin Burke , Frank Eriksson , C. B. Pipper

We give the new distribution named Gamma Lindley distribution (GaLD), of which the Lindley distribution (LD) is a particular case. In this paper, we discuss and add more properties. Also, an application of this distribution is given.

Applications · Statistics 2015-01-28 Halim Zeghdoudi , Sihem Nedjar

The property of extended longitudinal scaling of rapidity distributions was noticed recently over a broad range of beam energies. It is shown here that this property is consistent with predictions of the statistical thermal model up to the…

High Energy Physics - Phenomenology · Physics 2008-11-26 J. Cleymans , J. Strümpfer , L. Turko

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

Coronavirus COVID-19 spreads through the population mostly based on social contact. To gauge the potential for widespread contagion, to cope with associated uncertainty and to inform its mitigation, more accurate and robust modelling is…

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