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This paper focuses on nonparametric statistical inference of the hazard rate function of discrete distributions based on $\delta$-record data. We derive the explicit expression of the maximum likelihood estimator and determine its exact…

Statistics Theory · Mathematics 2025-04-03 Martín Alcalde , Miguel Lafuente , F. Javier López , Lina Maldonado , Gerardo Sanz

In this paper, we present methods of obtaining single moments of order statistics arising from posibly dependent and non-identically distributed discrete random variables. We derive exact and approximate formulas convenient for numerical…

Probability · Mathematics 2019-11-28 Anna Dembińska , Agnieszka Goroncy

Testing for conditional independence is a core aspect of constraint-based causal discovery. Although commonly used tests are perfect in theory, they often fail to reject independence in practice, especially when conditioning on multiple…

Machine Learning · Statistics 2019-03-13 Alexander Marx , Jilles Vreeken

Marginal imputation, which consists of imputing each item requiring imputation separately, is often used in surveys. This type of imputation procedures leads to asymptotically unbiased estimators of simple parameters such as population…

Methodology · Statistics 2015-11-04 Hélène Chaput , Guillaume Chauvet , David Haziza , Laurianne Salembier , Julie Solard

This paper investigates what can be inferred about an arbitrary continuous probability distribution from a finite sample of $N$ observations drawn from it. The central finding is that the $N$ sorted sample points partition the real line…

Machine Learning · Statistics 2025-07-30 Urban Eriksson

We investigate the problems of identity and closeness testing over a discrete population from random samples. Our goal is to develop efficient testers while guaranteeing Differential Privacy to the individuals of the population. We describe…

Machine Learning · Computer Science 2017-07-19 Maryam Aliakbarpour , Ilias Diakonikolas , Ronitt Rubinfeld

Let $\mathbf{X}(n) \in \mathbb{R}^d$ be a sequence of random vectors, where $n\in\mathbb{N}$ and $d = d(n)$. Under certain weakly dependence conditions, we prove that the distribution of the maximal component of $\mathbf{X}$ and the…

Probability · Mathematics 2025-04-22 Mikhail Isaev , Igor Rodionov , Rui-Ray Zhang , Maksim Zhukovskii

Regular variation provides a convenient theoretical framework to study large events. In the multivariate setting, the dependence structure of the positive extremes is characterized by a measure - the spectral measure - defined on the…

Machine Learning · Statistics 2021-02-24 Meyer Nicolas , Olivier Wintenberger

Two closely related discrete probability distributions are introduced. In each case the support is a set of vectors in $\mathbb{R}^n$ obtained from the partitions of the fixed positive integer $n$. These distributions arise naturally when…

Combinatorics · Mathematics 2021-07-09 Andrew V. Sills

Statistical matching is a technique for integrating two or more data sets when information available for matching records for individual participants across data sets is incomplete. Statistical matching can be viewed as a missing data…

Methodology · Statistics 2015-10-14 Jae-kwang Kim , Emily Berg , Taesung Park

In the context of this paper, a record is an entry in a sequence of random variables (RV's) that is larger or smaller than all previous entries. After a brief review of the classic theory of records, which is largely restricted to sequences…

Statistical Mechanics · Physics 2008-03-20 Joachim Krug

While supporting the execution of business processes, information systems record event logs. Conformance checking relies on these logs to analyze whether the recorded behavior of a process conforms to the behavior of a normative…

Artificial Intelligence · Computer Science 2020-07-07 Han van der Aa , Henrik Leopold , Matthias Weidlich

The estimation of information measures of continuous distributions based on samples is a fundamental problem in statistics and machine learning. In this paper, we analyze estimates of differential entropy in $K$-dimensional Euclidean space,…

Information Theory · Computer Science 2021-11-29 Georg Pichler , Pablo Piantanida , Günther Koliander

We consider two variables that are related to each other by an invertible function. While it has previously been shown that the dependence structure of the noise can provide hints to determine which of the two variables is the cause, we…

We establish properties of a new type of fractal which has partial self similarity at all scales. For any collection of iterated functions systems with an associated probability distribution and any positive integer V there is a…

Dynamical Systems · Mathematics 2008-02-04 Michael Barnsley , John E. Hutchinson , Örjan Stenflo

The identification of increasingly smaller signal from objects observed with a non-perfect instrument in a noisy environment poses a challenge for a statistically clean data analysis. We want to compute the probability of frequencies…

Astrophysics · Physics 2010-06-29 P. Reegen , M. Gruberbauer , L. Schneider , W. W. Weiss

Partial correlations quantify linear association between two variables adjusting for the influence of the remaining variables. They form the backbone for graphical models and are readily obtained from the inverse of the covariance matrix.…

Methodology · Statistics 2019-04-23 Ionas Erb

We review recent advances on the record statistics of strongly correlated time series, whose entries denote the positions of a random walk or a L\'evy flight on a line. After a brief survey of the theory of records for independent and…

Statistical Mechanics · Physics 2017-07-21 Claude Godreche , Satya N. Majumdar , Gregory Schehr

This work considers a problem of estimating a mixing probability density $f$ in the setting of discrete mixture models. The paper consists of three parts. The first part focuses on the construction of an $L_1$ consistent estimator of $f$.…

Information Theory · Computer Science 2021-05-11 Luc Devroye , Alex Dytso

Distance correlation is a measure of dependence between two paired random vectors or matrices of arbitrary, not necessarily equal, dimensions. Unlike Pearson correlation, the population distance correlation coefficient is zero if and only…

Methodology · Statistics 2025-06-19 Kontemeniotis Nikolaos , Vargiakakis Rafail , Tsagris Michail