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The Poisson-binomial distribution is useful in many applied problems in engineering, actuarial science, and data mining. The Poisson-binomial distribution models the distribution of the sum of independent but not identically distributed…

Computation · Statistics 2017-02-07 Man Zhang , Yili Hong , Narayanaswamy Balakrishnan

We study extremal statistics and return intervals in stationary long-range correlated sequences for which the underlying probability density function is bounded and uniform. The extremal statistics we consider e.g., maximum relative to…

Statistical Mechanics · Physics 2015-05-13 N. R. Moloney , J. Davidsen

We address the problem of estimating the Weibull tail-coefficient which is the regular variation exponent of the inverse failure rate function. We propose a family of estimators of this coefficient and an associate extreme quantile…

Methodology · Statistics 2024-09-04 Laurent Gardes , Stéphane Girard

We consider universal inference in variance components models, focusing on settings where the parameter is near or at the boundary of the parameter set. Two cases, which are not handled by existing state-of-the-art methods, are of…

Methodology · Statistics 2025-09-03 Yiqiao Zhang , Karl Oskar Ekvall , Aaron J. Molstad

The classical paradigm of scoring rules is to discriminate between two different forecasts by comparing them with observations. The probability distribution of the observed record is assumed to be perfect as a verification benchmark. In…

Methodology · Statistics 2021-08-06 Julie Bessac , Philippe Naveau

This paper introduces a new generalization of the flexible Weibull distribution with three parameters this model called the Marshall-Olkin flexible Weibull extension (MO-FWE) distribution which exhibits bathtub-shaped hazard rate. We…

Statistics Theory · Mathematics 2016-09-29 Abdelfattah Mustafa , B. S. El-Desouky , Shamsan AL-Garash

We provide a distribution-free test that can be used to determine whether any two joint distributions $p$ and $q$ are statistically different by inspection of a large enough set of samples. Following recent efforts from Long et al. [1], we…

Machine Learning · Computer Science 2016-07-26 Francesco Solera , Andrea Palazzi

The purpose of this paper is to propose methodologies for statistical inference of low-dimensional parameters with high-dimensional data. We focus on constructing confidence intervals for individual coefficients and linear combinations of…

Methodology · Statistics 2012-11-05 Cun-Hui Zhang , Stephanie S. Zhang

A fundamental class of inferential problems are those characterised by there having been a substantial degree of pre-data (or prior) belief that the value of a model parameter was equal or lay close to a specified value, which may, for…

Other Statistics · Statistics 2021-01-26 Russell J. Bowater

Profile likelihood intervals of large quantiles in Extreme Value distributions provide a good way to estimate these parameters of interest since they take into account the asymmetry of the likelihood surface in the case of small and…

Applications · Statistics 2010-05-21 A. Bolívar , E. Díaz-Francés , J. Ortega , E. Vilchis

In this paper, we introduce a new distribution called Burr III-Weibull(BW) distribution using the concept of competing risk. We derive moments, conditional moments, mean deviation and quantiles of the proposed distribution. Also the Renyi's…

Statistics Theory · Mathematics 2021-03-08 G S Deepthy , Nicy Sebastian , Reshma Rison

In engineering systems, it is usually assumed that lifetimes of components are independent and identically distributed (iid). But, the failure of a component results in a higher load on the remaining components and hence causes the…

Statistics Theory · Mathematics 2019-12-18 M. Doostparast , M. Hashempour , E. Velayati Moghaddam 1

In the statistical analysis of objects, samples and populations with quantitative variables, in many occasions we are interested in knowing the proportions that exist between the different variables from a same object; if these proportions…

Data Analysis, Statistics and Probability · Physics 2007-05-23 Enrique Ordaz Romay

The predominant method for evaluating the quality of causal models is to measure the graphical accuracy of the learned model structure. We present an alternative method for evaluating causal models that directly measures the accuracy of…

Artificial Intelligence · Computer Science 2016-08-17 Dan Garant , David Jensen

Probabilistic graphical models are a powerful concept for modeling high-dimensional distributions. Besides modeling distributions, probabilistic graphical models also provide an elegant framework for performing statistical inference;…

Artificial Intelligence · Computer Science 2022-09-13 Christian Knoll

Our interest is whether two binomial parameters differ, which parameter is larger, and by how much. This apparently simple problem was addressed by Fisher in the 1930's, and has been the subject of many review papers since then. Yet there…

Methodology · Statistics 2021-04-20 Michael P. Fay , Sally A. Hunsberger

This paper proposes a new approach for estimating the failure time distribution using the indicator data. The indicators, which are checked by periodic inspection of a standby redundant system, only convey whether at least one failure…

Other Computer Science · Computer Science 2016-02-19 Zheng Wang

This work studies the problem of content-based image retrieval, specifically, texture retrieval. It focuses on feature extraction and similarity measure for texture images. Our approach employs a recently developed method, the so-called…

Information Retrieval · Computer Science 2015-06-02 Alexander Sagel , Dominik Meyer , Hao Shen

Quantitative studies in many fields involve the analysis of multivariate data of diverse types, including measurements that we may consider binary, ordinal and continuous. One approach to the analysis of such mixed data is to use a copula…

Statistics Theory · Mathematics 2007-06-13 Peter D. Hoff

We apply the Weibull distribution -- a two-parameter family from extreme-value theory -- as a diagnostic framework for element-wise weight magnitude distributions in transformers. At initialization, i.i.d. Gaussian weights give |w| ~…

Machine Learning · Computer Science 2026-05-20 Tiexin Ding