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Inference over tails is usually performed by fitting an appropriate limiting distribution over observations that exceed a fixed threshold. However, the choice of such threshold is critical and can affect the inferential results. Extreme…

Statistical Finance · Quantitative Finance 2019-02-26 Chiara Lattanzi , Manuele Leonelli

The (conditional or unconditional) distribution of the continuous scan statistic in a one-dimensional Poisson process may be approximated by that of a discrete analogue via time discretization (to be referred to as the discrete…

Probability · Mathematics 2016-02-09 Yi-Ching Yao , Daniel Wei-Chung Miao , Xenos Chang-Shuo Lin

Heavy tailed distributions present a tough setting for inference. They are also common in industrial applications, particularly with Internet transaction datasets, and machine learners often analyze such data without considering the biases…

Applications · Statistics 2016-10-14 Matt Taddy , Hedibert Freitas Lopes , Matt Gardner

How to estimate the uncertainty of a given model is a crucial problem. Current calibration techniques treat different classes equally and thus implicitly assume that the distribution of training data is balanced, but ignore the fact that…

Computer Vision and Pattern Recognition · Computer Science 2023-04-14 Jiahao Chen , Bing Su

Computing and storing probabilities is a hard problem as soon as one has to deal with complex distributions over multiple random variables. The problem of efficient representation of probability distributions is central in term of…

Artificial Intelligence · Computer Science 2016-08-16 David Bellot , Pierre Bessiere

We develop a probabilistic method for assessing the tail behavior and geometric stability of one-dimensional n i.i.d. samples by tracking how their span contracts when the most extreme points are trimmed. Central to our approach is the…

Machine Learning · Statistics 2025-09-03 Erwan Dereure , Emmanuel Akame Mfoumou , David Holcman

Multivariate rapid variation describes decay rates of joint light tails of a multivariate distribution. We impose a local uniformity condition to control decay variation of distribution tails along different directions, and using…

Statistics Theory · Mathematics 2021-04-30 Haijun Li

Power law distributions, in particular Pareto distributions, describe data across diverse areas of study. We have developed a package in R to estimate the tail index for such datasets focusing on speed (in particular with large datasets),…

Methodology · Statistics 2020-06-19 Ranjiva Munasinghe , Pathum Kossinna , Dovini Jayasinghe , Dilanka Wijeratne

Many real-world prediction tasks have outcome variables that have characteristic heavy-tail distributions. Examples include copies of books sold, auction prices of art pieces, demand for commodities in warehouses, etc. By learning…

Machine Learning · Computer Science 2023-10-13 Xindi Wang , Onur Varol , Tina Eliassi-Rad

Estimating the tail index parameter is one of the primal objectives in extreme value theory. For heavy-tailed distributions the Hill estimator is the most popular way to estimate the tail index parameter. Improving the Hill estimator was…

Methodology · Statistics 2018-06-05 László Németh , András Zempléni

In this paper, an alternative mixed Poisson distribution is proposed by amalgamating Poisson distribution and a modification of the Quasi Lindley distribution. Some fundamental structural properties of the new distribution, namely the shape…

Methodology · Statistics 2021-10-26 Ramajeyam Tharshan , Pushpakanthie Wijekoon

In this paper we extend the refined second-order Poincar\'e inequality for Poisson functionals from a one-dimensional to a multi-dimensional setting. Its proof is based on a multivariate version of the Malliavin-Stein method for normal…

Probability · Mathematics 2021-11-23 Ehsan Azmoodeh , Mathias Mørck Ljungdahl , Christoph Thäle

Solving ill-posed inverse problems by Bayesian inference has recently attracted considerable attention. Compared to deterministic approaches, the probabilistic representation of the solution by the posterior distribution can be exploited to…

Numerical Analysis · Mathematics 2016-11-03 Felix Lucka

Counting experiments often rely on Monte Carlo simulations for predictions of Poisson expectations. The accompanying uncertainty from the finite Monte Carlo sample size can be incorporated into parameter estimation by modifying the Poisson…

Instrumentation and Methods for Astrophysics · Physics 2020-04-22 Thorsten Glüsenkamp

In this letter, we introduce an efficient method for estimating weight distributions of polar codes and polarization-adjusted convolutional (PAC) codes. Based on a recursive algorithm of computing the weight enumerating functions of polar…

Information Theory · Computer Science 2023-10-13 Junhua You , Shaohua Wu , Yajing Deng , Qinyu Zhang

Although linear regression models are fundamental tools in statistical science, the estimation results can be sensitive to outliers. While several robust methods have been proposed in frequentist frameworks, statistical inference is not…

Methodology · Statistics 2020-07-15 Shintaro Hashimoto , Shonosuke Sugasawa

Evaluating the Torontonian function is a central computational challenge in the simulation of Gaussian Boson Sampling (GBS) with threshold detection. In this work, we propose a recursive algorithm providing a polynomial speedup in the exact…

Quantum Physics · Physics 2022-11-16 Ágoston Kaposi , Zoltán Kolarovszki , Tamás Kozsik , Zoltán Zimborás , Péter Rakyta

We suggest a new hardcore Poisson-type distribution for Young diagrams with the row lengths from some finite list. A discrete variant of the time-ordered Mat\'{e}rn II process in 1D is employed. This approach is related to that based on the…

Combinatorics · Mathematics 2022-06-17 Ivan Cherednik

We calculate exact convergence times to reach random bipartite entanglement for various random protocols. The eigenproblem of a Markovian chain governing the process is mapped to a spin chain, thereby obtaining exact expression for the gap…

Quantum Physics · Physics 2008-09-26 Marko Znidaric

An expanded family of mixtures of multivariate power exponential distributions is introduced. While fitting heavy-tails and skewness has received much attention in the model-based clustering literature recently, we investigate the use of a…

Methodology · Statistics 2015-06-15 Utkarsh J. Dang , Ryan P. Browne , Paul D. McNicholas