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We propose a novel Bayesian approach to the problem of variable selection in multiple linear regression models. In particular, we present a hierarchical setting which allows for direct specification of a-priori beliefs about the number of…

Computation · Statistics 2019-03-14 Konstantin Posch , Maximilian Arbeiter , Jürgen Pilz

We consider a random walk on a homogeneous space $G/\Lambda$ where $G$ is a non-compact simple Lie group and $\Lambda$ is a lattice. The walk is driven by a probability measure $\mu$ on $G$ whose support generates a Zariski-dense subgroup.…

Dynamical Systems · Mathematics 2026-05-27 Timothée Bénard , Weikun He

We make two closely related theoretical contributions to the use of importance sampling schemes. First, for independent sampling, we prove that the minimax optimal trial distribution coincides with the target if and only if the target…

Computation · Statistics 2025-06-25 Quan Zhou

In this paper we study the Metropolis algorithm in connection with two mean--field spin systems, the so called mean--field Ising model and the Blume--Emery--Griffiths model. In both this examples the naive choice of proposal chain gives…

Probability · Mathematics 2007-05-23 Bassetti Federico , Leisen Fabrizio

For random-walk Metropolis (RWM) and parallel tempering (PT) algorithms, an asymptotic acceptance rate of around 0.234 is known to be optimal in certain high-dimensional limits. However, its practical relevance is uncertain due to…

Computation · Statistics 2025-08-05 Aidan Li , Liyan Wang , Tianye Dou , Jeffrey S. Rosenthal

We consider the problem of sampling from a strongly log-concave density in $\mathbb{R}^d$, and prove a non-asymptotic upper bound on the mixing time of the Metropolis-adjusted Langevin algorithm (MALA). The method draws samples by…

Machine Learning · Statistics 2019-12-12 Raaz Dwivedi , Yuansi Chen , Martin J. Wainwright , Bin Yu

High-dimensional distributions, especially those with heavy tails, are notoriously difficult for off-the-shelf MCMC samplers: the combination of unbounded state spaces, diminishing gradient information, and local moves results in…

Computation · Statistics 2024-02-22 Jun Yang , Krzysztof Łatuszyński , Gareth O. Roberts

The random walk process in a nonhomogeneous medium, characterised by a L\'evy stable distribution of jump length, is discussed. The width depends on a position: either before the jump or after that. In the latter case, the density slope is…

Statistical Mechanics · Physics 2017-03-29 Tomasz Srokowski

We introduce a multidimensional walk with memory and random tendency. The asymptotic behaviour is characterized, proving a law of large numbers and showing a phase transition from diffusive to superdiffusive regimes. In first case, we…

Probability · Mathematics 2020-10-09 Manuel González-Navarrete

Pseudo-marginal Metropolis-Hastings (pmMH) is a versatile algorithm for sampling from target distributions which are not easy to evaluate point-wise. However, pmMH requires good proposal distributions to sample efficiently from the target,…

Computation · Statistics 2018-07-30 Johan Dahlin , Adrian Wills , Brett Ninness

The purpose of this paper is to introduce a new Markov chain Monte Carlo method and exhibit its efficiency by simulation and high-dimensional asymptotic theory. Key fact is that our algorithm has a reversible proposal transition kernel,…

Methodology · Statistics 2014-12-22 Kengo Kamatani

As social network analysis (SNA) has drawn much attention in recent years, one bottleneck of SNA is these network data are too massive to handle. Furthermore, some network data are not accessible due to privacy problems. Therefore, we have…

Social and Information Networks · Computer Science 2022-05-13 Xiao Qi

We develop lagged Metropolis-Hastings walk for sampling from simple undirected graphs according to given stationary sampling probabilities. We explain how to apply the technique together with designed graphs for sampling of units-in-space.…

Methodology · Statistics 2022-05-16 Li-Chun Zhang

MCMC algorithms such as Metropolis-Hastings algorithms are slowed down by the computation of complex target distributions as exemplified by huge datasets. We offer in this paper an approach to reduce the computational costs of such…

Computation · Statistics 2014-06-11 Marco Banterle , Clara Grazian , Christian P. Robert

We study the dynamics of a deterministic walk confined in a narrow two-dimensional space randomly filled with point-like targets. At each step, the walker visits the nearest target not previously visited. Complex dynamics is observed at…

Disordered Systems and Neural Networks · Physics 2009-11-13 Denis Boyer

An algorithm for sampling from non-log-concave multivariate distributions is proposed, which improves the adaptive rejection Metropolis sampling (ARMS) algorithm by incorporating the hit and run sampling. It is not rare that the ARMS is…

Computation · Statistics 2015-03-10 Huaiye Zhang , Yuefeng Wu , Lulu Cheng , Inyoung Kim

Consider the following computational problem: given a regular digraph $G=(V,E)$, two vertices $u,v \in V$, and a walk length $t\in \mathbb{N}$, estimate the probability that a random walk of length $t$ from $u$ ends at $v$ to within $\pm…

Computational Complexity · Computer Science 2021-11-04 Edward Pyne , Salil Vadhan

We study the asymptotic behavior of the simple random walk on oriented versions of $\mathbb{Z}^2$. The considered lattices are not directed on the vertical axis but unidirectional on the horizontal one, with random orientations whose…

Probability · Mathematics 2007-05-23 Nadine Guillotin-Plantard , Arnaud Le Ny

We study a symmetric random walk (RW) in one spatial dimension in environment, formed by several zones of finite width, where the probability of transition between two neighboring points and corresponding diffusion coefficient are…

Statistical Mechanics · Physics 2017-04-03 A. V. Nazarenko , V. Blavatska

Fix integers $d \geq 2$ and $k\geq d-1$. Consider a random walk $X_0, X_1, \ldots$ in $\mathbb{R}^d$ in which, given $X_0, X_1, \ldots, X_n$ ($n \geq k$), the next step $X_{n+1}$ is uniformly distributed on the unit ball centred at $X_n$,…

Probability · Mathematics 2020-01-16 Francis Comets , Mikhail V. Menshikov , Andrew R. Wade