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Hilbert space combines the properties of two fundamentally different types of mathematical spaces: vector space and metric space. While the vector-space aspects of Hilbert space, such as formation of linear combinations of state vectors,…

Quantum Physics · Physics 2015-05-27 I. D'Amico , J. P. Coe , V. V. Franca , K. Capelle

This paper presents a selective survey of recent developments in statistical inference and multiple testing for high-dimensional regression models, including linear and logistic regression. We examine the construction of confidence…

Methodology · Statistics 2023-01-26 T. Tony Cai , Zijian Guo , Yin Xia

The spiked Fisher matrix is a significant topic for two-sample problems in multivariate statistical inference. This paper is dedicated to testing the number of spikes in a high-dimensional generalized spiked Fisher matrix that relaxes the…

Statistics Theory · Mathematics 2025-02-26 Rui Wang , Dandan Jiang

Quantum Graphical Models (QGMs) generalize classical graphical models by adopting the formalism for reasoning about uncertainty from quantum mechanics. Unlike classical graphical models, QGMs represent uncertainty with density matrices in…

Machine Learning · Statistics 2018-10-31 Siddarth Srinivasan , Carlton Downey , Byron Boots

The properties of a hard-sphere fluid in contact with hard spherical and cylindrical walls are studied. Rosenfeld's density functional theory (DFT) is applied to determine the density profile and surface tension $\gamma$ for wide ranges of…

Statistical Mechanics · Physics 2007-05-23 P. Bryk , R. Roth , K. R. Mecke , S. Dietrich

We develop some graph-based tests for spherical symmetry of a multivariate distribution using a method based on data augmentation. These tests are constructed using a new notion of signs and ranks that are computed along a path obtained by…

Statistics Theory · Mathematics 2024-12-10 Bilol Banerjee , Anil K. Ghosh

This paper is devoted to the study of the general linear hypothesis testing (GLHT) problem of multi-sample high-dimensional mean vectors. For the GLHT problem, we introduce a test statistic based on $L^2$-norm and random integration method,…

Statistics Theory · Mathematics 2024-10-22 Mingxiang Cao , Yelong Qiu , Junyong Park

The spectral density matrix is a fundamental object of interest in time series analysis, and it encodes both contemporary and dynamic linear relationships between component processes of the multivariate system. In this paper we develop…

Statistics Theory · Mathematics 2025-02-04 Jinyuan Chang , Qing Jiang , Tucker S. McElroy , Xiaofeng Shao

Stochastic center manifolds theory are crucial in modelling the dynamical behavior of complex systems under stochastic influences. A multiplicative ergodic theorem on Hilbert space is proved to be satisfied to the exponential trichotomy…

Dynamical Systems · Mathematics 2013-10-16 Xiaopeng Chen , Anthony J. Roberts , Jinqiao Duan

Among a family of 2-parameter left invariant metrics on Sp(2), we determine which have nonnegative sectional curvatures and which are Einstein. On the quotiente $\widetilde{N}^{11}=(Sp(2)\times S^4)/S^3$, we construct a homogeneous…

Differential Geometry · Mathematics 2020-04-29 Chao Qian , Zizhou Tang , Wenjiao Yan

We develop a test for spherical symmetry of a multivariate distribution $\Pr$ that works well even when the dimension of the data $d$ is larger than the sample size $n$. We propose a non-negative measure of spherical asymmetry $\zeta(\Pr)$…

Statistics Theory · Mathematics 2025-09-09 Bilol Banerjee , Anil K. Ghosh

This paper introduces $\infty$-Diff, a generative diffusion model defined in an infinite-dimensional Hilbert space, which can model infinite resolution data. By training on randomly sampled subsets of coordinates and denoising content only…

Machine Learning · Computer Science 2024-03-04 Sam Bond-Taylor , Chris G. Willcocks

To characterize the location (mean, median) of a set of graphs, one needs a notion of centrality that is adapted to metric spaces, since graph sets are not Euclidean spaces. A standard approach is to consider the Fr\'echet mean. In this…

Social and Information Networks · Computer Science 2021-06-01 Daniel Ferguson , François G. Meyer

In statistics, independent, identically distributed random samples do not carry a natural ordering, and their statistics are typically invariant with respect to permutations of their order. Thus, an $n$-sample in a space $M$ can be…

Statistics Theory · Mathematics 2023-12-08 Philipp Harms , Peter W. Michor , Xavier Pennec , Stefan Sommer

We develop non-asymptotically justified methods for hypothesis testing about the $p-$dimensional coefficients $\theta^{*}$ in (possibly nonlinear) regression models. Given a function $h:\,\mathbb{R}^{p}\mapsto\mathbb{R}^{m}$, we consider…

Statistics Theory · Mathematics 2019-07-01 Ying Zhu

The paper is centered around a new proof of the infinitesimal rigidity of smooth closed surfaces with everywhere positive Gauss curvature. We use a reformulation that replaces deformation of an embedding by deformation of the metric inside…

Differential Geometry · Mathematics 2011-05-26 Ivan Izmestiev

We address data-driven learning of the infinitesimal generator of stochastic diffusion processes, essential for understanding numerical simulations of natural and physical systems. The unbounded nature of the generator poses significant…

Machine Learning · Statistics 2024-05-22 Vladimir R. Kostic , Karim Lounici , Helene Halconruy , Timothee Devergne , Massimiliano Pontil

We construct a new random probability measure on the sphere and on the unit interval which in both cases has a Gibbs structure with the relative entropy functional as Hamiltonian. It satisfies a quasi-invariance formula with respect to the…

Probability · Mathematics 2007-05-23 Max-K von Renesse , Karl-Theodor Sturm

We present a complete classification of Einstein metrics on the space M = I \times S^3, where I is the interval (0,l) or (0,\infty) or their closures, and we consider separate metric functions f and h (functions of I) for the base and fiber…

Differential Geometry · Mathematics 2011-11-10 Curtis T. Asplund , Brian Krummel , Evan Merrell , Robert Rachal , DaGang Yang

It is developed a Riemannian reformulation of classical statistical mechanics for systems in thermodynamic equilibrium, which arises as a natural extension of Ruppeiner geometry of thermodynamics. The present proposal leads to interpret…

Statistical Mechanics · Physics 2010-11-19 L Velazquez
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