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Recent attention in quickest change detection in the multi-sensor setting has been on the case where the densities of the observations change at the same instant at all the sensors due to the disruption. In this work, a more general…

Information Theory · Computer Science 2016-11-18 Vasanthan Raghavan , Venugopal V. Veeravalli

In this study, we introduce the first-of-its-kind class of tests for detecting change points in the distribution of a sequence of independent matrix-valued random variables. The tests are constructed using the weighted square integral…

Methodology · Statistics 2024-01-02 Žikica Lukić , Bojana Milošević

Methods for detecting structural changes, or change points, in time series data are widely used in many fields of science and engineering. This chapter sketches some basic methods for the analysis of structural changes in time series data.…

Statistical Finance · Quantitative Finance 2018-08-28 Christian Kleiber

The Switch Point Algorithm is a new approach for solving optimal control problems whose solutions are either singular or bang-bang or both singular and bang-bang, and which possess a finite number of jump discontinuities in an optimal…

Optimization and Control · Mathematics 2021-07-20 Mahya Aghaee , William W. Hager

Understanding the stochastic behavior of currency exchange rates is critical for assessing financial stability and anticipating market transitions. In this study, we investigate the empirical dynamics of the USD exchange rate in three…

Statistical Finance · Quantitative Finance 2025-07-04 Yazdan Babazadeh Maghsoodlo , Amin Safaeesirat

In this article we suggest a new statistical approach considering survival heterogeneity as a breakpoint model in an ordered sequence of time to event variables. The survival responses need to be ordered according to a numerical covariate.…

Applications · Statistics 2016-09-26 Olivier Bouaziz , Grégory Nuel

In this work we propose a Bayesian framework for data fusion of multivariate signals which arises in imaging systems. More specifically, we consider the case where we have observed two images of the same object through two different imaging…

Data Analysis, Statistics and Probability · Physics 2007-05-23 Olivier Feron , Ali Mohammad-Djafari

We consider Markov-switching regression models, i.e. models for time series regression analyses where the functional relationship between covariates and response is subject to regime switching controlled by an unobservable Markov chain.…

Methodology · Statistics 2015-05-12 Roland Langrock , Thomas Kneib , Richard Glennie , Théo Michelot

We present a systematic algorithm testing for the existence of collective self-organization in the behavior of agents in social systems, with a concrete empirical implementation on the Dow Jones Industrial Average index (DJIA) over the 20th…

Statistical Mechanics · Physics 2008-12-10 D. Sornette , W. -X. Zhou

In the current work we present two generalizations of the Parallel Tempering algorithm, inspired by the so-called continuous-time Infinite Swapping algorithm. Such a method, found its origins in the molecular dynamics community, and can be…

Numerical Analysis · Mathematics 2021-10-13 Jonas Latz , Juan P. Madrigal-Cianci , Fabio Nobile , Raul Tempone

This paper analyzes the process of long-run co-movements and stock market globalization on the basis of cointegration tests and vector error correction (VEC) models. The cointegration tests used here allow for structural breaks to be…

Statistical Finance · Quantitative Finance 2011-01-24 Rui Menezes , Andreia Dioniso

Modeling the dynamics of non-stationary stochastic systems requires balancing the representational power of deep learning with the mathematical transparency of classical models. While classical Markov transition operators provide explicit,…

Machine Learning · Computer Science 2026-05-07 Jan Rovirosa , Jesse Schmolze

Finding a ground state of a given Hamiltonian of an Ising model on a graph $G=(V,E)$ is an important but hard problem. The standard approach for this kind of problem is the application of algorithms that rely on single-spin-flip Markov…

Dynamic jumps in the price and volatility of an asset are modelled using a joint Hawkes process in conjunction with a bivariate jump diffusion. A state space representation is used to link observed returns, plus nonparametric measures of…

Applications · Statistics 2016-03-10 Worapree Maneesoonthorn , Catherine S. Forbes , Gael M. Martin

We provide a hybrid method that captures the polynomial speed of convergence and polynomial speed of mixing for Markov processes. The hybrid method that we introduce is based on the coupling technique and renewal theory. We propose to…

Numerical Analysis · Mathematics 2017-11-07 Yao Li , Hui Xu

A $k$-height on a graph $G=(V, E)$ is an assignment $V\to\{0, \ldots, k\}$ such that the value on ajacent vertices differs by at most $1$. We study the Markov chain on $k$-heights that in each step selects a vertex at random, and, if…

Discrete Mathematics · Computer Science 2024-10-14 Stefan Felsner , Daniel Heldt , Sandro Roch , Peter Winkler

A spin system is studied, with simultaneous permutation-symmetric Potts and spin-rotation-symmetric clock interactions, in spatial dimensions d=2 and 3. The global phase diagram is calculated from the renormalizaton-group solution with the…

Statistical Mechanics · Physics 2023-09-12 E. Can Artun , A. Nihat Berker

Specialized classifiers, namely those dedicated to a subset of classes, are often adopted in real-world recognition systems. However, integrating such classifiers is nontrivial. Existing methods, e.g. weighted average, usually implicitly…

Machine Learning · Computer Science 2017-09-08 Zhizhong Li , Dahua Lin

Stock price change in financial market occurs through transactions in analogy with diffusion in stochastic physical systems. The analysis of price changes in real markets shows that long-range correlations of price fluctuations largely…

Statistical Mechanics · Physics 2008-12-10 V. Gontis

We develop a mixture procedure for multi-sensor systems to monitor data streams for a change-point that causes a gradual degradation to a subset of the streams. Observations are assumed to be initially normal random variables with known…

Machine Learning · Statistics 2016-02-19 Yang Cao , Yao Xie , Nagi Gebraeel
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