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We develop a weighted local likelihood estimate for the parameters that govern the local spatial dependency of a locally stationary random field. The advantage of this local likelihood estimate is that it smoothly downweights the influence…

Methodology · Statistics 2009-11-03 Ethan Anderes , Michael Stein

We simulate static memory materials on a two-dimensional lattice. The bulk properties of such materials depend on boundary conditions. Considerable information can be stored in various local patterns. We observe local probabilities…

Statistical Mechanics · Physics 2018-02-26 D. Sexty , C. Wetterich

A new transient effective theory of the relativistic Boltzmann equation is derived for locally momentum-anisotropic systems. In the expansion of the distribution function around a local "quasi-equilibrium" state a non-hydrodynamic dynamical…

Nuclear Theory · Physics 2016-02-26 Dennis Bazow , Mauricio Martinez , Ulrich W. Heinz

We study the fluctuations of a random surface in a stochastic growth model on a system of interlacing particles placed on a two dimensional lattice. There are two different types of particles, one with a low jump rate and the other with a…

Mathematical Physics · Physics 2015-03-19 Maurice Duits

Motivated by the problem of testing for the existence of a signal of known parametric structure and unknown ``location'' (as explained below) against a noisy background, we obtain for the maximum of a centered, smooth random field an…

Statistics Theory · Mathematics 2008-06-27 Yuval Nardi , David O. Siegmund , Benjamin Yakir

Ground motion scenarios exists for most of the seismically active areas around the globe. They essentially correspond to shaking level maps at given earthquake return times which are used as reference for the likely areas under threat from…

Applications · Statistics 2020-04-02 Luigi Lombardo , Hakan Tanyas

In many networks such as transportation or communication networks, distance is certainly a relevant parameter. In addition, real-world examples suggest that when long-range links are existing, they usually connect to hubs-the well connected…

Disordered Systems and Neural Networks · Physics 2009-11-07 Marc Barthelemy

Random walks represent an important tool for probing the structural and dynamical properties of networks and modeling transport and diffusion processes on networks. However, when individuals' movement becomes dictated by more complicated…

Pattern Formation and Solitons · Physics 2022-11-24 Per Sebastian Skardal

Irregularly sampling a spatially stationary random field does not yield a graph stationary signal in general. Based on this observation, we build a definition of graph stationarity based on intrinsic stationarity, a less restrictive…

Signal Processing · Electrical Eng. & Systems 2018-09-26 Alexander Serrano , Benjamin Girault , Antonio Ortega

Binomial random intersection graphs can be used as parsimonious statistical models of large and sparse networks, with one parameter for the average degree and another for transitivity, the tendency of neighbours of a node to be connected.…

Social and Information Networks · Computer Science 2018-06-26 Joona Karjalainen , Lasse Leskelä

We introduce the extremal range, a local statistic for studying the spatial extent of extreme events in random fields on $\mathbb{R}^d$. Conditioned on exceedance of a high threshold at a location $s$, the extremal range at $s$ is the…

Statistics Theory · Mathematics 2024-11-06 Ryan Cotsakis , Elena Di Bernardino , Thomas Opitz

This contribution reports on numerical simulations of 2D granular flows on erodible beds. The broad aim is to investigate whether simple flows of model granular matter exhibits spontaneous oscillatory motion in generic flow conditions, and…

Soft Condensed Matter · Physics 2012-11-27 Lydie Staron

We consider bond percolation on the square lattice with perfectly correlated random probabilities. According to scaling considerations, mapping to a random walk problem and the results of Monte Carlo simulations the critical behavior of the…

Statistical Mechanics · Physics 2009-11-07 Róbert Juhász , Ferenc Iglói

For spatiotemporal chaos described by partial differential equations, there are generally locations where the dynamical variable achieves its local extremum or where the time partial derivative of the variable vanishes instantaneously. To a…

Chaotic Dynamics · Physics 2013-03-07 Quntao Zhuang , Xun Gao , Qi Ouyang , Hongli Wang

Oscillatory dynamics are ubiquitous in biological networks. Possible sources of oscillations are well understood in low-dimensional systems, but have not been fully explored in high-dimensional networks. Here we study large networks…

Disordered Systems and Neural Networks · Physics 2016-12-21 Célian Bimbard , Erwan Ledoux , Srdjan Ostojic

Monte Carlo simulations and dynamical mean-field approximations are performed to study the phase transitions in rock-scissors-paper game on different host networks. These graphs are originated from lattices by introducing quenched and…

Statistical Mechanics · Physics 2009-11-10 Attila Szolnoki , Gyorgy Szabo

For more than a century lattice random walks have been employed ubiquitously, both as a theoretical laboratory to develop intuition about more complex stochastic processes and as a tool to interpret a vast array of empirical observations.…

Statistical Mechanics · Physics 2024-12-31 Luca Giuggioli , Seeralan Sarvaharman , Debraj Das , Daniel Marris , Toby Kay

In Puplinskaite and Surgailis (2014) we introduced the notion of scaling transition for stationary random fields $X$ on $\mathbb{Z}^2$ in terms of partial sums limits, or scaling limits, of $X$ over rectangles whose sides grow at possibly…

Statistics Theory · Mathematics 2014-12-09 Donata Puplinskaite , Donatas Surgailis

We study the maximal displacement of branching random walks in a class of time inhomogeneous environments. Specifically, binary branching random walks with Gaussian increments will be considered, where the variances of the increments change…

Probability · Mathematics 2011-12-07 Ofer Zeitouni , Ming Fang

Latent space models are popular for analyzing dynamic network data. We propose a variational approach to estimate the model parameters as well as the latent positions of the nodes in the network. The variational approach is much faster than…

Methodology · Statistics 2021-06-01 Yan Liu , Yuguo Chen
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