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We propose a sequential test for detecting arbitrary distribution shifts that allows conformal test martingales (CTMs) to work under a fixed, reference-conditional setting. Existing CTM detectors construct test martingales by continually…

Machine Learning · Computer Science 2026-02-17 Shalev Shaer , Yarin Bar , Drew Prinster , Yaniv Romano

We study locally interacting processes in discrete time, often called probabilistic cellular automata, indexed by locally finite graphs. For infinite regular trees and certain generalized Galton-Watson trees, we show that the marginal…

Probability · Mathematics 2025-10-28 Daniel Lacker , Kavita Ramanan , Ruoyu Wu

We investigate analytical properties of free stable distributions and discover many connections with their classical counterparts. Our main result is an explicit formula for the Mellin transform, which leads to explicit series…

Probability · Mathematics 2024-03-19 Takahiro Hasebe , Alexey Kuznetsov

We derive the exact probability density function of the product of $N$ independent variance-gamma random variables with zero location parameter. We then apply this formula to derive formulas for the cumulative distribution function and…

Probability · Mathematics 2025-08-05 Robert E. Gaunt , Siqi Li , Heather Sutcliffe

Meta-analyses are regarded as the highest level in the hierarchy of evidence, yet standard models traditionally concentrated on estimating the mean effect size, often under restrictive assumptions about the underlying distribution, such as…

Other Statistics · Statistics 2026-04-02 Yefeng Yang , Shinichi Nakagawa

Random contractions (sub-unitary random matrices) appear naturally when considering quantized chaotic maps within a general theory of open linear stationary systems with discrete time. We analyze statistical properties of complex…

Chaotic Dynamics · Physics 2009-10-31 Yan V. Fyodorov , H. -J. Sommmers

Let $X$ and $Y$ be independent variance-gamma random variables with zero location parameter; then the exact probability density function of the product $XY$ is derived. Some basic distributional properties are also derived, including…

Probability · Mathematics 2024-05-14 Robert E. Gaunt , Siqi Li

The framework of distribution testing is currently ubiquitous in the field of property testing. In this model, the input is a probability distribution accessible via independently drawn samples from an oracle. The testing task is to…

Data Structures and Algorithms · Computer Science 2022-09-22 Sourav Chakraborty , Eldar Fischer , Arijit Ghosh , Gopinath Mishra , Sayantan Sen

The behaviour of statistical relational representations across differently sized domains has become a focal area of research from both a modelling and a complexity viewpoint.Recently, projectivity of a family of distributions emerged as a…

Artificial Intelligence · Computer Science 2024-08-21 Felix Weitkämper

Extended geometric distribution is defined and its mixture is characterized by the property of having completely monotone probability sequence. Also, convolution equations and probability generating functions are used to characterize…

Statistics Theory · Mathematics 2007-06-13 E Sandhya , S Sherly , M K Jos , N Raju

A stochastic model, the product of a circulant matrix and a random normal vector, is shown to produce an evolutive long memory time series with a power law spectral density. The distribution of the time series, a beta location scale family…

General Mathematics · Mathematics 2026-02-26 Robert Kimberk

We characterise the learning of a mixture of two clouds of data points with generic centroids via empirical risk minimisation in the high dimensional regime, under the assumptions of generic convex loss and convex regularisation. Each cloud…

Machine Learning · Statistics 2024-03-19 Urte Adomaityte , Gabriele Sicuro , Pierpaolo Vivo

Delayed processes are ubiquitous throughout biology. These delays may arise through maturation processes or as the result of complex multi-step networks, and mathematical models with distributed delays are increasingly used to capture the…

Populations and Evolution · Quantitative Biology 2024-10-15 Tyler Cassidy

Uncertainty associated with statistical problems arises due to what has not been seen as opposed to what has been seen. Using probability to quantify the uncertainty the task is to construct a probability model for what has not been seen…

Methodology · Statistics 2025-01-06 Fuheng Cui , Stephen G. Walker

Model explainability is crucial for human users to be able to interpret how a proposed classifier assigns labels to data based on its feature values. We study generalized linear models constructed using sets of feature value rules, which…

Machine Learning · Statistics 2023-11-06 Sanjeeb Dash , Soumyadip Ghosh , Joao Goncalves , Mark S. Squillante

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

High frequency data in finance have led to a deeper understanding on probability distributions of market prices. Several facts seem to be well stablished by empirical evidence. Specifically, probability distributions have the following…

Statistical Mechanics · Physics 2009-10-31 Jaume Masoliver , Miquel Montero , Josep M. Porra

Let $q\ge2$ be an integer, $\{X_n\}_{n\geq 1}$ a stochastic process with state space $\{0,\ldots,q-1\}$, and $F$ the cumulative distribution function (CDF) of $\sum_{n=1}^\infty X_n q^{-n}$. We show that stationarity of $\{X_n\}_{n\geq 1}$…

Probability · Mathematics 2022-08-12 Horia Cornean , Ira W. Herbst , Jesper Møller , Benjamin Støttrup , Kasper S. Sørensen

In the setting of entangled single-sample distributions, the goal is to estimate some common parameter shared by a family of distributions, given one \emph{single} sample from each distribution. We study mean estimation and linear…

Machine Learning · Computer Science 2020-07-08 Hui Yuan , Yingyu Liang

A class of discrete distributions can be derived from stationary renewal processes. They have the useful property that the mean is a simple function of the model parameters. Thus regressions of the distribution mean on covariates can be…

Methodology · Statistics 2018-03-01 Rose Baker
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