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Product-form stationary distributions in Markov chains have been a foundational advance and driving force in our understanding of stochastic systems. In this paper, we introduce a new product-form relationship that we call "graph-based…

Probability · Mathematics 2025-11-03 Céline Comte , Isaac Grosof

We study continuous processes indexed by a special family of graphs. Processes indexed by vertices of graphs are known as probabilistic graphical models. Burdzy and Pal in their paper proposed a continuous version of graphical models --…

Probability · Mathematics 2016-12-26 Tvrtko Tadić

Switching dynamical systems are an expressive model class for the analysis of time-series data. As in many fields within the natural and engineering sciences, the systems under study typically evolve continuously in time, it is natural to…

Machine Learning · Computer Science 2022-05-19 Lukas Köhs , Bastian Alt , Heinz Koeppl

There have been rapid developments in model-based clustering of graphs, also known as block modelling, over the last ten years or so. We review different approaches and extensions proposed for different aspects in this area, such as the…

Machine Learning · Statistics 2020-01-01 Clement Lee , Darren J Wilkinson

Motivated by applications in movement ecology, in this paper I propose a new class of integrated continuous-time hidden Markov models in which each observation depends on the underlying state of the process over the whole interval since the…

Methodology · Statistics 2019-10-01 Paul G Blackwell

An inductive probabilistic classification rule must generally obey the principles of Bayesian predictive inference, such that all observed and unobserved stochastic quantities are jointly modeled and the parameter uncertainty is fully…

Machine Learning · Statistics 2015-03-25 Henrik Nyman , Jie Xiong , Johan Pensar , Jukka Corander

We introduce a general approach for modeling the dynamic of multivariate time series when the data are of mixed type (binary/count/continuous). Our method is quite flexible and conditionally on past values, each coordinate at time $t$ can…

Methodology · Statistics 2021-04-05 Zinsou Max Debaly , Lionel Truquet

This paper generalizes the notion of stochastic order to a relation between probability measures over arbitrary measurable spaces. This generalization is motivated by the observation that for the stochastic ordering of two stationary Markov…

Probability · Mathematics 2008-06-24 Lasse Leskelä

In this paper we consider the issue of a unique prediction in one to one two sided matching markets, as defined by Gale and Shapley (1962), and we prove the following. Theorem. Let P be a one-to-one two-sided matching market and let P be…

Theoretical Economics · Economics 2023-07-21 Gregory Z. Gutin , Philip R. Neary , Anders Yeo

Time-evolving random graph models have appeared and have been studied in various fields of research over the past decades. However, the rigorous mathematical treatment of large graphs and their limits at the process-level is still in its…

Probability · Mathematics 2021-04-28 Adrian Röllin , Zhuo-Song Zhang

We introduce a multivariate hidden Markov model to jointly cluster time-series observations with different support, i.e. circular and linear. Relying on the general projected normal distribution, our approach allows for bimodal and/or…

Applications · Statistics 2015-01-27 Gianluca Mastrantonio , Antonello Maruotti , Giovanna Jona Lasinio

Joint models are well suited to modelling linked data from laboratories and health registers. However, there are few examples of joint models that allow for (a) multiple markers, (b) multiple survival outcomes (including terminal events,…

In this paper, we study discrete Lyapunov models, which consist of steady-state distributions of first-order vector autoregressive models. The parameter matrix of such a model encodes a directed graph whose vertices correspond to the…

We consider Markov Decision Processes (MDPs) in which every stationary policy induces the same graph structure for the underlying Markov chain and further, the graph has the following property: if we replace each recurrent class by a node,…

Machine Learning · Computer Science 2021-03-10 Joseph Lubars , Anna Winnicki , Michael Livesay , R. Srikant

We consider the problem of model selection in Gaussian Markov fields in the sample deficient scenario. In many practically important cases, the underlying networks are embedded into Euclidean spaces. Using the natural geometric structure,…

Machine Learning · Statistics 2018-10-31 Ilya Soloveychik , Vahid Tarokh

We introduce graphical time series models for the analysis of dynamic relationships among variables in multivariate time series. The modelling approach is based on the notion of strong Granger causality and can be applied to time series…

Statistics Theory · Mathematics 2011-07-18 Michael Eichler

This paper integrates two strands of the literature on stability of general state Markov chains: conventional, total variation based results and more recent order-theoretic results. First we introduce a complete metric over Borel…

Probability · Mathematics 2024-10-02 Takashi Kamihigashi , John Stachurski

We show that the ratio of matched individuals to blocking pairs grows linearly with the number of propose--accept rounds executed by the Gale--Shapley algorithm for the stable marriage problem. Consequently, the participants can arrive at…

Data Structures and Algorithms · Computer Science 2012-05-15 Patrik Floréen , Petteri Kaski , Valentin Polishchuk , Jukka Suomela

We consider the problem of sequential matching in a stochastic block model with several classes of nodes and generic compatibility constraints. When the probabilities of connections do not scale with the size of the graph, we show that…

Probability · Mathematics 2026-01-14 Nahuel Soprano-Loto , Matthieu Jonckheere , Pascal Moyal

Recent work has discussed the importance of multiplicative closure for the Markov models used in phylogenetics. For continuous-time Markov chains, a sufficient condition for multiplicative closure of a model class is ensured by demanding…

Populations and Evolution · Quantitative Biology 2012-04-24 Jeremy Sumner , Jesus Fernandez-Sanchez , Peter Jarvis
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