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We describe here a new method to estimate copula measure. From N observations of two variables X and Y, we draw a huge number m of subsamples (size n<N), and we compute the joint ranks in these subsamples. Then, for each bivariate rank…

Methodology · Statistics 2007-09-26 Jérôme Collet

We consider the problem of estimating a low rank covariance function $K(t,u)$ of a Gaussian process $S(t), t\in [0,1]$ based on $n$ i.i.d. copies of $S$ observed in a white noise. We suggest a new estimation procedure adapting…

Statistics Theory · Mathematics 2015-04-14 Vladimir Koltchinskii , Karim Lounici , Alexander B. Tsybakov

Partial integrability in phase-oscillator dynamics is typically examined for identically connected oscillators or groups thereof. Yet, the precise connectivity conditions that ensure conserved quantities on general networks remain unclear.…

Adaptation and Self-Organizing Systems · Physics 2025-12-01 Vincent Thibeault , Benjamin Claveau , Antoine Allard , Patrick Desrosiers

A powerful tool for the analysis of nonrandomized observational studies has been the potential outcomes model. Utilization of this framework allows analysts to estimate average treatment effects. This article considers the situation in…

Statistics Theory · Mathematics 2019-05-31 Debashis Ghosh , Efrén Cruz-Cortés

We present a collective coordinate approach to describe coupled phase oscillators. We apply the method to study synchronisation in a Kuramoto model. In our approach an N-dimensional Kuramoto model is reduced to an n-dimensional ordinary…

Pattern Formation and Solitons · Physics 2015-05-21 Georg A. Gottwald

This article considers Hamiltonian mechanical systems with potential functions admitting jump discontinuities. The focus is on accurate and efficient numerical approximations of their solutions, which will be defined via the laws of…

Numerical Analysis · Mathematics 2022-01-05 Molei Tao , Shi Jin

We consider the problem of global synchronization in a large random network of Kuramoto oscillators where some of them are subject to an external periodically driven force. We explore a recently proposed dimensional reduction approach and…

Adaptation and Self-Organizing Systems · Physics 2019-07-31 Joyce S. Climaco , Alberto Saa

The performance of known and new parametric estimators for Archimedean copulas is investigated, with special focus on large dimensions and numerical difficulties. In particular, method-of-moments-like estimators based on pairwise Kendall's…

Computation · Statistics 2012-11-05 Marius Hofert , Martin Maechler , Alexander J. McNeil

The understanding of synchronization ranging from natural to social systems has driven the interests of scientists from different disciplines. Here, we have investigated the synchronization dynamics of the Kuramoto dynamics departing from…

Disordered Systems and Neural Networks · Physics 2009-09-29 Jie Ren , Huijie Yang

Parameterized systems of polynomial equations arise in many applications in science and engineering with the real solutions describing, for example, equilibria of a dynamical system, linkages satisfying design constraints, and scene…

Machine Learning · Statistics 2022-08-09 Edgar A. Bernal , Jonathan D. Hauenstein , Dhagash Mehta , Margaret H. Regan , Tingting Tang

We study synchronization of Kuramoto oscillators in strongly modular networks in which the structure of the network inside each community is averaged. We find that the dynamics of the interacting communities can be described as an ensemble…

Adaptation and Self-Organizing Systems · Physics 2012-06-19 Per Sebastian Skardal , Juan G. Restrepo

Low-rank tensor approximations have shown great potential for uncertainty quantification in high dimensions, for example, to build surrogate models that can be used to speed up large-scale inference problems (Eigel et al., Inverse Problems…

Numerical Analysis · Mathematics 2020-11-30 Paul B. Rohrbach , Sergey Dolgov , Lars Grasedyck , Robert Scheichl

We study the problem of high-dimensional covariance estimation under the constraint that the partial correlations are nonnegative. The sign constraints dramatically simplify estimation: the Gaussian maximum likelihood estimator is well…

Statistics Theory · Mathematics 2020-07-31 Jake A. Soloff , Adityanand Guntuboyina , Michael I. Jordan

In view of highly decentralized and diversified power generation concepts, in particular with renewable energies such as wind and solar power, the analysis and control of the stability and the synchronization of power networks is an…

Disordered Systems and Neural Networks · Physics 2018-11-14 Volker Mehrmann , Riccardo Morandin , Simona Olmi , Eckehard Schöll

Confidence interval procedures used in low dimensional settings are often inappropriate for high dimensional applications. When a large number of parameters are estimated, marginal confidence intervals associated with the most significant…

Methodology · Statistics 2017-02-24 Jean Morrison , Noah Simon

Efficient methods for the simulation of quantum circuits on classic computers are crucial for their analysis due to the exponential growth of the problem size with the number of qubits. Here we study lumping methods based on bisimulation,…

Maintaining the stability of synchronization state is crucial for the functioning of many natural and artificial systems. In this study, we develop methods to optimize the synchronization stability of the Kuramoto model by minimizing the…

Optimization and Control · Mathematics 2017-01-18 Bo Li , K. Y. Michael Wong

This article reviews recent progress in high-dimensional bootstrap. We first review high-dimensional central limit theorems for distributions of sample mean vectors over the rectangles, bootstrap consistency results in high dimensions, and…

Statistics Theory · Mathematics 2022-05-20 Victor Chernozhukov , Denis Chetverikov , Kengo Kato , Yuta Koike

The Kuramoto model captures various synchronization phenomena in biological and man-made systems of coupled oscillators. It is well-known that there exists a critical coupling strength among the oscillators at which a phase transition from…

Dynamical Systems · Mathematics 2011-05-06 Florian Dorfler , Francesco Bullo

Density estimation plays a key role in many tasks in machine learning, statistical inference, and visualization. The main bottleneck in high-dimensional density estimation is the prohibitive computational cost and the slow convergence rate.…

Machine Learning · Computer Science 2021-10-22 Liang Ding , Lu Zou , Wenjia Wang , Shahin Shahrampour , Rui Tuo