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This paper introduces constrained mixtures for continuous distributions, characterized by a mixture of distributions where each distribution has a shape similar to the base distribution and disjoint domains. This new concept is used to…

Machine Learning · Statistics 2015-03-29 Conrado S. Miranda , Fernando J. Von Zuben

As a new method for detecting change-points in high-resolution time series, we apply Maximum Mean Discrepancy to the distributions of ordinal patterns in different parts of a time series. The main advantage of this approach is its…

Methodology · Statistics 2012-10-19 Mathieu Sinn , Ali Ghodsi , Karsten Keller

Across the sciences, the statistical analysis of networks is central to the production of knowledge on relational phenomena. Because of their ability to model the structural generation of networks, exponential random graph models are a…

Data Analysis, Statistics and Probability · Physics 2015-05-27 Bruce A. Desmarais , Skyler J. Cranmer

Traditional survival analysis techniques focus on the occurrence of failures over the time. During analysis of such events, ignoring the related unobserved covariates or heterogeneity involved in data sample may leads us to adverse…

Methodology · Statistics 2021-12-22 Shikhar Tyagi , Arvind Pandey , David D Hanagal

In this work, a novel approach for the construction and training of time series models is presented that deals with the problem of learning on large time series with non-equispaced observations, which at the same time may possess features…

Machine Learning · Computer Science 2020-11-25 Charilaos Mylonas , Eleni Chatzi

In this work we present a simple estimation procedure for a general frailty model for analysis of prospective correlated failure times. Earlier work showed this method to perform well in a simulation study. Here we provide rigorous…

Statistics Theory · Mathematics 2007-06-13 David M. Zucker , Malka Gorfine , Li Hsu

Despite rapid advances in AI, safety remains the main bottleneck to deploying machine-learning systems. A critical safety component is out-of-distribution detection: given an input, decide whether it comes from the same distribution as the…

Machine Learning · Computer Science 2025-11-06 Joonas Järve , Karl Kaspar Haavel , Meelis Kull

The mathematical properties of a family of generalized beta distribution, including beta-normal, skewed-t, log-F, beta-exponential, beta-Weibull distributions have recently been studied in several publications. This paper applies these…

Methodology · Statistics 2007-10-26 J. H. Sepanski , Lingji Kong

Compound Poisson distributions have been employed by many authors to fit experimental data, typically via the method of moments or maximum likelihood estimation. We propose a new technique and apply it to several sets of published data. It…

Methodology · Statistics 2025-04-01 S. R. Mane

This work introduces a novel methodology based on finite mixtures of Student-t distributions to model the errors' distribution in linear regression models. The novelty lies on a particular hierarchical structure for the mixture distribution…

Methodology · Statistics 2017-11-15 Nívea B. da Silva , Marcos O. Prates , Flávio B. Gonçalves

Another new family of continuous probability distribution is proposed by using Generalized Marshal-Olkin distribution as the base line distribution in the Kumaraswamy-G distribution. This family includes (Cordeiro and de Castro, 2011) and…

Statistics Theory · Mathematics 2016-09-16 Laba Handique , Subrata Chakraborty

We consider three new classes of exponential dispersion models of discrete probability distributions which are defined by specifying their variance functions in their mean value parameterization. In a previous paper (Bar-Lev and Ridder,…

Methodology · Statistics 2020-04-01 Shaul K. Bar-Lev , Ad Ridder

Nonlinear ordinary differential equations (ODEs) are powerful tools for modeling real-world dynamical systems. However, propagating initial state uncertainty through nonlinear dynamics, especially when the ODE is unknown and learned from…

Systems and Control · Electrical Eng. & Systems 2026-02-06 Peter Amorese , Morteza Lahijanian

This article describes a multivariate polynomial regression method where the uncertainty of the input parameters are approximated with Gaussian distributions, derived from the central limit theorem for large weighted sums, directly from the…

Machine Learning · Statistics 2013-10-04 Peter Kovesarki , Ian C. Brock

In this study an attempt has been made to propose a way to develop new distribution. For this purpose, we need only idea about distribution function. Some important statistical properties of the new distribution like moments, cumulants,…

Methodology · Statistics 2024-08-30 Brijesh P. Singh , Utpal Dhar Das

Sine-skewed circular distributions are identifiable and have easily-computable trigonometric moments and a simple random number generation algorithm, whereas they are known to have relatively low levels of asymmetry. This study proposes a…

Methodology · Statistics 2024-02-16 Yoichi Miyata , Takayuki Shiohama , Toshihiro Abe

In this paper, we consider the order statistics from a newly-introduced lifetime distribution called the XLindley distribution. We have derived explicit closed form expressions for the single moments and product moments of order statistics…

Methodology · Statistics 2025-02-11 Zuber Akhter , S. M. T. K. MirMostafaee , Abu Bakar , Ehsan Ormoz

The lifetimes of subjects which are left-censored lie below a threshold value or a limit of detection. A popular tool used to handle left-censored data is the reversed hazard rate. In this work, we study the properties and develop…

Statistics Theory · Mathematics 2022-12-27 G. Asha , Durga Vasudevan

Optimization is widely used in statistics, and often efficiently delivers point estimates on useful spaces involving structural constraints or combinatorial structure. To quantify uncertainty, Gibbs posterior exponentiates the negative loss…

Methodology · Statistics 2025-07-23 Cheng Zeng , Eleni Dilma , Jason Xu , Leo L Duan

From the integration of non-symmetrical hyperboles, a one-parameter generalization of the logarithmic function is obtained. Inverting this function, one obtains the generalized exponential function. We show that functions characterizing…

Data Analysis, Statistics and Probability · Physics 2010-10-19 Alexandre Souto Martinez , Rodrigo Silva Gonzalez , Cesar Augusto Sangaletti Tercariol