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The discrete moment problem is a foundational problem in distribution-free robust optimization, where the goal is to find a worst-case distribution that satisfies a given set of moments. This paper studies the discrete moment problems with…

Optimization and Control · Mathematics 2017-08-08 Xi Chen , Simai He , Bo Jiang , Christopher Thomas Ryan , Teng Zhang

We deduce the non-asymptotical (bilateral) estimates for moment inequalities for multiple sums of non-negative (more precisely, non-negative) independent random variables, on the other words, the well known U or V-statistics. Our…

Probability · Mathematics 2018-01-24 E. Ostrovsky , L. Sirota

Under reasonable algebraic assumptions and under an infinite second order moment assumption, we show that the logarithm of the norm (log-norm) of a product of random i.i.d. matrices with entries in $\mathbb{R}$ or in any other local field…

Probability · Mathematics 2026-01-09 Axel Péneau

In this article, a generalized inverse xgamma distribution (GIXGD) has been introduced as the generalized version of the inverse xgamma distribution. The proposed model exhibits the pattern of non-monotone hazard rate and belongs to family…

Methodology · Statistics 2018-12-13 Harsh Tripathi , Abhimanyu Singh Yadav , Mahendra Saha , Sumit Kumar

Discrete-state stochastic models have become a well-established approach to describe biochemical reaction networks that are influenced by the inherent randomness of cellular events. In the last years severalmethods for accurately…

Molecular Networks · Quantitative Biology 2017-07-03 Alexander Lück , Verena Wolf

This paper introduces the multivariate tail-inflated normal (MTIN) distribution, an elliptical heavy-tails generalization of the multivariate normal (MN). The MTIN belongs to the family of MN scale mixtures by choosing a convenient…

Methodology · Statistics 2020-06-23 Antonio Punzo , Luca Bagnato

As the unification of various models of ordered quantities, generalized order statistics act as a simplistic approach introduced in \cite{kamps1995concept}. In this present study, results pertaining to the expressions of marginal and joint…

Methodology · Statistics 2025-02-04 Neetu Gupta , S. K. Neogy , Qazi J. Azhad , Bhagwati Devi

We study truncated moment sequences of distribution mixtures, especially from Gaussian and log-normal distributions and their Carath\'eodory numbers. For $\mathsf{A} = \{a_1,\dots,a_m\}$ continuous (sufficiently differentiable) functions on…

Probability · Mathematics 2019-07-01 Philipp J. di Dio

For two families of beta distributions, we show that the generalized Stieltjes transforms of their elements may be written as elementary functions (powers and fractions) of the Stieltjes transform of the Wigner distribution. In particular,…

Classical Analysis and ODEs · Mathematics 2016-04-13 Nizar Demni

In this work, we define a family of probability densities involving the generalized trigonometric functions defined by Dr\'abek and Man\'asevich [1], which we name Generalized Trigonometric Densities. We show their relationship with the…

Mathematical Physics · Physics 2025-04-01 David Puertas-Centeno , Steeve Zozor

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

This paper is devoted to reduce the conservatism of distributionally robust optimization with moments information. Since the optimal solution of distributionally robust optimization is required to be feasible for all uncertain distributions…

Optimization and Control · Mathematics 2020-08-20 Ke-wei Ding , Nan-jing Huang , Lei Wang

This paper is devoted to a fractional generalization of the Dirichlet distribution. The form of the multivariate distribution is derived assuming that the $n$ partitions of the interval $[0,W_n]$ are independent and identically distributed…

Probability · Mathematics 2021-02-17 Elvira Di Nardo , Federico Polito , Enrico Scalas

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

Enduring violent conflicts are interrupted by lulls without violence. Studies of interevent times found power law distributions based on coarse-grained data with a resolution of one day. Fine-grained data of violence with a resolution of…

Physics and Society · Physics 2026-04-14 Jeroen Bruggeman

In this work, we define the notions of Wronskian and simplified Wronskian for Stieltjes derivatives and study some of their properties in a similar manner to the context of time scales or the usual derivative. Later, we use these tools to…

Classical Analysis and ODEs · Mathematics 2022-06-23 Francisco J. Fernández , Ignacio Marquez Albés , F. Adrián F. Tojo

The study of long-horizon returns has received a great deal of attention in recent years (see, for example, Boudoukh, Richardson, and Whitelaw (2008), Neuberger (2012) and Lee (2013), Fama and French (2018)). While most of the discussions…

Risk Management · Quantitative Finance 2022-01-20 Hwai-Chung Ho

We address the challenges of modeling high-frequency integer price changes in financial markets using continuous distributions, particularly the Student's t-distribution. We demonstrate that traditional GARCH models, which rely on…

Statistical Finance · Quantitative Finance 2025-10-14 Vladimír Holý

The universality for the eigenvalue spacing statistics of generalized Wigner matrices was established in our previous work \cite{EYY} under certain conditions on the probability distributions of the matrix elements. A major class of…

Mathematical Physics · Physics 2011-09-27 László Erdos , Horng-Tzer Yau , Jun Yin

We consider a lognormal diffusion process having a multisigmoidal logistic mean, useful to model the evolution of a population which reaches the maximum level of the growth after many stages. Referring to the problem of statistical…