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Related papers: On the equivalence of probability spaces

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From a suitable integral representation of the Laplace transform of a positive semi-definite quadratic form of independent real random variables with not necessarily identical densities a univariate integral representation is derived for…

Statistics Theory · Mathematics 2007-11-01 T. Royen

In this work we present iterated function systems with general measures(IFSm) formed by a set of maps $\tau_{\lambda}$ acting over a compact space $X$, for a compact space of indices, $\Lambda$. The Markov process $Z_k$ associated to the…

Dynamical Systems · Mathematics 2025-05-15 Elismar R. Oliveira , Rafael R. Souza

Under mirror symmetry a non-Fano variety $X$ corresponds to an instanton corrected Hori-Vafa potential $W$. The classical period of $W$ equals the regularized quantum period of $X$, which is a generating function for descendant…

Algebraic Geometry · Mathematics 2025-02-28 Per Berglund , Tim Gräfnitz , Michael Lathwood

For a Dunford-Schwartz operator in a fully symmetric space of measurable functions of an arbitrary measure space, we prove pointwise convergence of the conventional and weighted ergodic averages.

Functional Analysis · Mathematics 2017-01-01 Vladimir Chilin , Dogan Comez , Semyon Litvinov

Recently, Chernozhukov, Chetverikov, and Kato [Ann. Statist. 42 (2014) 1564--1597] developed a new Gaussian comparison inequality for approximating the suprema of empirical processes. This paper exploits this technique to devise sharp…

Statistics Theory · Mathematics 2017-05-30 Fang Han , Sheng Xu , Wen-Xin Zhou

We prove that if $q_1, \ldots, q_m: {\Bbb R}^n \longrightarrow {\Bbb R}$ are quadratic forms in variables $x_1, \ldots, x_n$ such that each $q_k$ depends on at most $r$ variables and each $q_k$ has common variables with at most $r$ other…

Probability · Mathematics 2020-02-19 Alexander Barvinok

We study Gauss quadrature for Freud weights and derive worst case error estimates for functions in a family of associated Sobolev spaces. For the Gaussian weight $e^{-\pi x^2}$ these spaces coincide with a class of modulation spaces which…

Numerical Analysis · Mathematics 2022-08-03 Martin Ehler , Karlheinz Gröchenig

A new class of fractional-order stochastic evolution equations of the form $(\partial_t + A)^\gamma X(t) = \dot{W}^Q(t)$, $t\in[0,T]$, $\gamma \in (0,\infty)$, is introduced, where $-A$ generates a $C_0$-semigroup on a separable Hilbert…

Probability · Mathematics 2026-01-06 Kristin Kirchner , Joshua Willems

A method to perform unfolding with Gaussian processes (GPs) is presented. Using Bayesian regression, we define an estimator for the underlying truth distribution as the mode of the posterior. We show that in the case where the bin contents…

Data Analysis, Statistics and Probability · Physics 2018-11-07 Adam Bozson , Glen Cowan , Francesco Spanò

In the article, Besov-Orlicz regularity of sample paths of stochastic processes that are represented by multiple integrals of order $n\in\mathbb{N}$ is treated. We give sufficient conditions for the considered processes to have paths in the…

Probability · Mathematics 2021-11-25 Petr Čoupek , Martin Ondreját

Random variables $X^i$, $i=1,2$ are 'probabilistically equivalent' if they have the same law. Moreover, in any class of equivalent random variables it is easy to select canonical representatives. The corresponding questions are more…

Probability · Mathematics 2024-04-10 Mathias Beiglböck , Gudmund Pammer , Stefan Schrott , Xin Zhang

Let $\nu_{\alpha,q}$ be the probability and orthogonality measure for the $q$-Meixner-Pollaczek orthogonal polynomials, which has appeared in \cite{BEH15} as the distribution of the $(\alpha,q)$-Gaussian process (the Gaussian process of…

Functional Analysis · Mathematics 2017-04-04 Nobuhiro Asai , Marek Bożejko , Takahiro Hasebe

This work brings together two powerful concepts in Gaussian processes: the variational approach to sparse approximation and the spectral representation of Gaussian processes. This gives rise to an approximation that inherits the benefits of…

Machine Learning · Statistics 2017-11-09 James Hensman , Nicolas Durrande , Arno Solin

Gaussian processes are a key component of many flexible statistical and machine learning models. However, they exhibit cubic computational complexity and high memory constraints due to the need of inverting and storing a full covariance…

Machine Learning · Statistics 2025-10-07 Teemu Härkönen , Sara Wade , Kody Law , Lassi Roininen

We establish It\^o's formula along flows of probability measures associated with general semimartingales; this generalizes existing results for flows of measures on It\^o processes. Our approach is to first establish It\^o's formula for…

Probability · Mathematics 2022-09-20 Xin Guo , Huyên Pham , Xiaoli Wei

Let $P_n$ and $Q_n$ be two probability measures representing two different probabilistic models of some system (e.g., an $n$-particle equilibrium system, a set of random graphs with $n$ vertices, or a stochastic process evolving over a time…

Statistical Mechanics · Physics 2023-03-30 Hugo Touchette

Let X be a second order random process indexed by a compact interval [0,T]. Assume that n independent realizations of X are observed on a fixed grid of p time points. Under mild regularity assumptions on the sample paths of X, we show the…

Statistics Theory · Mathematics 2011-05-25 David Degras

Gaussian wavepackets are a popular tool for semiclassical analyses of classically chaotic systems. We demonstrate that they are extremely powerful in the semiquantal analysis of such systems, too, where their dynamics can be recast in an…

chao-dyn · Physics 2009-10-22 Arjendu K. Pattanayak , William C. Schieve

In this article, we present some specific aspects of symmetric Gamma process mixtures for use in regression models. We propose a new Gibbs sampler for simulating the posterior and we establish adaptive posterior rates of convergence related…

Statistics Theory · Mathematics 2016-07-29 Zacharie Naulet , Eric Barat

Given two measurable spaces $H$ and $D$ with countably generated $\sigma$-algebras, a perfect prior probability measure $P_H$ on $H$ and a sampling distribution $S: H \rightarrow D$, there is a corresponding inference map $I: D \rightarrow…

Category Theory · Mathematics 2018-08-16 Jared Culbertson , Kirk Sturtz