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We consider a sequential Bayesian changepoint detection problem for a general stochastic model, assuming that the observed data may be dependent and non-identically distributed and the prior distribution of the change point is arbitrary,…

Statistics Theory · Mathematics 2016-01-15 Alexander G. Tartakovsky

We study theoretically, experimentally and numerically the probability distribution $F(t_f|x_0,L)$ of the first passage times $t_f$ needed by a freely diffusing Brownian particle to reach a target at a distance $L$ from the initial position…

Statistical Mechanics · Physics 2021-07-21 Benjamin Besga , Felix Faisant , Artyom Petrosyan , Sergio Ciliberto , Satya N. Majumdar

This paper presents a novel formula for the transition density of the Brownian motion on a sphere of any dimension and discusses an algorithm for the simulation of the increments of the spherical Brownian motion based on this formula. The…

Statistical Mechanics · Physics 2025-04-01 Aleksandar Mijatović , Veno Mramor , Gerónimo Uribe Bravo

We consider the problem of efficient financial surveillance aimed at "on-the-go" detection of structural breaks (anomalies) in "live"-monitored financial time series. With the problem approached statistically, viz. as that of multi-cyclic…

Applications · Statistics 2015-12-04 Andrey Pepelyshev , Aleksey S. Polunchenko

We consider a random model for directed graphs whereby an arc is placed from one vertex to another with a prescribed probability which may vary from arc to arc. Using perturbation bounds as well as Chernoff inequalities, we show that the…

Probability · Mathematics 2013-09-20 Franklin H. J. Kenter

Standard diffusion models for graph generation typically rely on uniform time-stepping, an approach that overlooks the non-homogeneous dynamics of distributional evolution on complex manifolds. In this paper, we present an…

Machine Learning · Statistics 2026-05-04 Yuhui Lu , Wenjing Liu , Kun Zhan

We introduce an extension of finite mixture models by incorporating skew-normal distributions within a Hidden Markov Model framework. By assuming a constant transition probability matrix and allowing emission distributions to vary according…

Methodology · Statistics 2025-09-25 Andrea Nigri , Marco Forti , Han Lin Shang

We introduce a location statistic for distributions on non-linear geometric spaces, the diffusion mean, serving as an extension and an alternative to the Fr\'echet mean. The diffusion mean arises as the generalization of Gaussian maximum…

Statistics Theory · Mathematics 2022-12-06 Benjamin Eltzner , Pernille Hansen , Stephan F. Huckemann , Stefan Sommer

Systems where resource availability approaches a critical threshold are common to many engineering and scientific applications and often necessitate the estimation of first passage time statistics of a Brownian motion (Bm) driven by…

Statistical Mechanics · Physics 2011-04-05 Annalisa Molini , Peter Talkner , Gabriel G. Katul , Amilcare Porporato

Sequential change-point detection for graphs is a fundamental problem for streaming network data types and has wide applications in social networks and power systems. Given fixed vertices and a sequence of random graphs, the objective is to…

Statistics Theory · Mathematics 2021-02-12 Liyan Xie , Yao Xie

First passage time models describe the time it takes for a random process to exit a region of interest and are widely used across various scientific fields. Fast and accurate numerical methods for computing the likelihood function in these…

Methodology · Statistics 2025-12-17 Sicheng Liu , Alexander Fengler , Michael J. Frank , Matthew T. Harrison

We calculate the probability distribution function (PDF) of an overdamped Brownian particle moving in a periodic potential energy landscape $U(x)$. The PDF is found by solving the corresponding Smoluchowski diffusion equation. We derive the…

Statistical Mechanics · Physics 2018-11-21 Matan Sivan , Oded Farago

This study explores a Gaussian quasi-likelihood approach for estimating parameters of diffusion processes with Markovian regime switching. Assuming the ergodicity under high-frequency sampling, we will show the asymptotic normality of the…

Statistics Theory · Mathematics 2025-05-19 Yuzhong Cheng , Hiroki Masuda

We employ distribution regression (DR) to estimate the joint distribution of two outcome variables conditional on chosen covariates. While Bivariate Distribution Regression (BDR) is useful in a variety of settings, it is particularly…

Assume that there are multiple data streams (channels, sensors) and in each stream the process of interest produces generally dependent and non-identically distributed observations. When the process is in a normal mode (in-control), the…

Statistics Theory · Mathematics 2018-07-25 Alexander Tartakovsky

A Langevin process diffusing in a periodic potential landscape has a time dependent diffusion constant which means that its average mean squared displacement (MSD) only becomes linear at late times. The long time, or effective diffusion…

Statistical Mechanics · Physics 2015-06-19 David S. Dean , Gleb Oshanin

In the present work, we explore homogenization techniques for a class of switching diffusion processes whose drift and diffusion coefficients, and jump intensities are smooth, spatially periodic functions; we assume full coupling between…

Probability · Mathematics 2025-07-01 Chetan D. Pahlajani

We consider the first exit time of a Shiryaev-Roberts diffusion with constant positive drift from the interval $[0,A]$ where $A>0$. We show that the moment generating function (Laplace transform) of a suitably standardized version of the…

Methodology · Statistics 2017-03-07 Aleksey S. Polunchenko

This paper derives several formulae for the probability that a Wiener process, which has a stochastic drift and random variance, crosses a one-sided stochastic boundary within a finite time interval. A non-explicit formula is first obtained…

Probability · Mathematics 2024-10-04 Yoann Potiron

We propose a method to infer the presence and location of change-points in the distribution of a sequence of independent data taking values in a general metric space, where change-points are viewed as locations at which the distribution of…

Methodology · Statistics 2020-01-15 Paromita Dubey , Hans-Georg Müller