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The Bernstein-von Mises theorem (BvM) gives conditions under which the posterior distribution of a parameter $\theta\in\Theta\subseteq\mathbb R^d$ based on $n$ independent samples is asymptotically normal. In the high-dimensional regime, a…

Statistics Theory · Mathematics 2024-11-05 Anya Katsevich

Few methods in Bayesian non-parametric statistics/ machine learning have received as much attention as Bayesian Additive Regression Trees (BART). While BART is now routinely performed for prediction tasks, its theoretical properties began…

Statistics Theory · Mathematics 2019-05-10 Veronika Rockova

A characterization of noncontextual models which fall within the ambit of Fine's theorem is provided. In particular, the equivalence between the existence of three notions is made explicit: a joint probability distribution over the outcomes…

Quantum Physics · Physics 2015-02-13 Ravi Kunjwal

This paper aims to examine the characteristics of the posterior distribution of covariance/precision matrices in a "large $p$, large $n$" scenario, where $p$ represents the number of variables and $n$ is the sample size. Our analysis…

Statistics Theory · Mathematics 2026-02-02 Partha Sarkar , Kshitij Khare , Malay Ghosh , Matt P. Wand

In a smooth semiparametric estimation problem, the marginal posterior for the parameter of interest is expected to be asymptotically normal and satisfy frequentist criteria of optimality if the model is endowed with a suitable prior. It is…

Statistics Theory · Mathematics 2012-05-30 P. J. Bickel , B. J. K. Kleijn

State-space models (SSMs) provide a flexible framework for modelling time-series data. Consequently, SSMs are ubiquitously applied in areas such as engineering, econometrics and epidemiology. In this paper we provide a fast approach for…

Machine Learning · Statistics 2018-11-22 Tom Ryder , Andrew Golighty , A. Stephen McGough , Dennis Prangle

Statistical Inference is the process of determining a probability distribution over the space of parameters of a model given a data set. As more data becomes available this probability distribution becomes updated via the application of…

Disordered Systems and Neural Networks · Physics 2022-04-28 David S. Berman , Jonathan J. Heckman , Marc Klinger

This is a systematic introduction for physicists to the theory of algebras and groups with braid statistics, as developed over the last three years by the author. There are braided lines, braided planes, braided matrices and braided groups…

High Energy Physics - Theory · Physics 2008-02-03 Shahn Majid

Economic systems are similar with physic systems for their large number of individuals and the exist of equilibrium. In this paper, we present a model applying the equilibrium statistical model in economic systems. Consistent with…

General Finance · Quantitative Finance 2015-04-17 Zhiwu Zheng

The distributional statistical framework replaces classical probability densities by distribution-kernel pairs $(T, \varphi)$, where $T$ is a tempered distribution and $\varphi$ is a rapidly decaying kernel. We develop the thesis that the…

Statistics Theory · Mathematics 2026-05-26 R. Labouriau

Quantum mechanics provides a statistical description about nature, and thus would be incomplete if its statistical predictions could not be accounted for some realistic models with hidden variables. There are, however, two powerful theorems…

We introduce a ``Statistical Query Sampling'' model, in which the goal of an algorithm is to produce an element in a hidden set $Ssubseteqbit^n$ with reasonable probability. The algorithm gains information about $S$ through oracle calls…

Quantum Physics · Physics 2016-11-18 Avrim Blum , Ke Yang

We illustrate how dynamical transitions in nonlinear semiclassical models can be recognized as phase transitions in the corresponding -- inherently linear -- quantum model, where, in a Statistical Mechanics framework, the thermodynamic…

Statistical Mechanics · Physics 2011-12-05 Pierfrancesco Buonsante , Vittorio Penna , Alessandro Vezzani

Within the so-called scaled quantum theory, the standard bouncing ball problem is analyzed under the presence of a gravitational field and harmonic potential. In this framework, the quantum-classical transition of the density matrix is…

Quantum Physics · Physics 2024-10-25 S. V. Mousavi , S. Miret-Artés

In the quantum-Bayesian approach to quantum foundations, a quantum state is viewed as an expression of an agent's personalist Bayesian degrees of belief, or probabilities, concerning the results of measurements. These probabilities obey the…

Quantum Physics · Physics 2015-05-14 Christopher A. Fuchs , Ruediger Schack

Physics relies on mathematical spaces carefully matched to the phenomena under study. Phase space in classical mechanics, Hilbert space in quantum theory, configuration spaces in field theory all provide representations in which physical…

Other Quantitative Biology · Quantitative Biology 2026-01-23 Arturo Tozzi

Several arguments demonstrate the incompatibility between Quantum Mechanics and classical Physics. Bell's inequalities and Greenberger-Horne-Zeilinger (GHZ) arguments apply to specific non-classical states. The Kochen-Specker (KS) one,…

Quantum Physics · Physics 2024-11-28 Alejandro Hnilo

Descriptions of molecular systems usually refer to two distinct theoretical frameworks. On the one hand the quantum pure state, i.e. the wavefunction, of an isolated system which is determined to calculate molecular properties and to…

Statistical Mechanics · Physics 2011-03-17 Barbara Fresch , Giorgio J. Moro

In the 1920's, the English philosopher W.E. Johnson introduced a characterization of the symmetric Dirichlet prior distribution in terms of its predictive distribution. This is typically referred to as Johnson's "sufficientness" postulate,…

Statistics Theory · Mathematics 2021-11-05 Federico Camerlenghi , Stefano Favaro

The classical Hennessy-Milner theorem is an important tool in the analysis of concurrent processes; it guarantees that any two non-bisimilar states in finitely branching labelled transition systems can be distinguished by a modal formula.…

Logic in Computer Science · Computer Science 2022-08-31 Jonas Forster , Sergey Goncharov , Dirk Hofmann , Pedro Nora , Lutz Schröder , Paul Wild