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Concentration inequalities, a major tool in probability theory, quantify how much a random variable deviates from a certain quantity. This paper proposes a systematic convex optimization approach to studying and generating concentration…

Probability · Mathematics 2024-08-30 Celine Moucer , Adrien Taylor , Francis Bach

Let $\mathcal{M}_n(E)$ denote the set of vectors of the first $n$ moments of probability measures on $E\subset\mathbb{R}$ with existing moments. The investigation of such moment spaces in high dimension has found considerable interest in…

Probability · Mathematics 2018-05-31 Holger Dette , Dominik Tomecki , Martin Venker

The theory of holomorphic functions of several complex variables is applied in proving a multidimensional variant of a theorem involving an exponential boundedness criterion for the classical moment problem. A theorem of Petersen concerning…

Quantum Physics · Physics 2009-11-07 Anatolij Dvurecenskij , Pekka Lahti , Kari Ylinen

The generalized problem of moments is a conic linear optimization problem over the convex cone of positive Borel measures with given support. It has a large variety of applications, including global optimization of polynomials and rational…

Optimization and Control · Mathematics 2018-11-14 Etienne de Klerk , Monique Laurent

We present an analytic method for computing the moments of a sum of independent and identically distributed random variables. The limiting behavior of these sums is very important to statistical theory, and the moment expressions that we…

Statistics Theory · Mathematics 2012-01-17 Daniel M. Packwood

We consider random coefficient autoregressive models of infinite order (AR($\infty$)) under the assumption of non-negativity of the coefficients. We develop novel methods yielding sufficient or necessary conditions for finiteness of…

Probability · Mathematics 2024-09-17 Pascal Maillard , Olivier Wintenberger

Theoretical results for importance sampling rely on the existence of certain moments of the importance weights, which are the ratios between the proposal and target densities. In particular, a finite variance ensures square root convergence…

Methodology · Statistics 2013-07-31 Michael K. Pitt , Minh-Ngoc Tran , Marcel Scharth , Robert Kohn

The discrete data encoded in the power moments of a positive measure, fast decaying at infinity on euclidean space, is incomplete for recovery, leading to the concept of moment indeterminateness. On the other hand, classical integral…

Functional Analysis · Mathematics 2023-08-01 David P. Kimsey , Mihai Putinar

The probability `measure' for measurements at two consecutive moments of time is non-additive. These probabilities, on the other hand, may be determined by the limit of relative frequency of measured events, which are by nature additive. We…

Quantum Physics · Physics 2009-11-10 Charis Anastopoulos

We consider the problem of guessing the realization of a random variable but under more general Tsallis' non-extensive entropic framework rather than the classical Maxwell-Boltzman-Gibbs-Shannon framework. We consider both the conditional…

Information Theory · Computer Science 2019-05-21 Abhik Ghosh

We study some connections between the random moment problem and the random matrix theory. A uniform draw in a space of moments can be lifted into the spectral probability measure of the pair (A,e) where A is a random matrix from a classical…

Probability · Mathematics 2009-09-29 Fabrice Gamboa , Alain Rouault

In order to study how well a finite group might be generated by repeated random multiplications, P. Diaconis suggested the following urn model. An urn contains some balls labeled by elements which generate a group G. Two are drawn at random…

Probability · Mathematics 2007-05-23 Aaron Abrams , Henry Landau , Zeph Landau , James Pommersheim , Eric Zaslow

A broad set of sufficient conditions that guarantees the existence of the maximum entropy (maxent) distribution consistent with specified bounds on certain generalized moments is derived. Most results in the literature are either focused on…

Information Theory · Computer Science 2009-09-29 Prakash Ishwar , Pierre Moulin

Models phrased though moment conditions are central to much of modern inference. Here these moment conditions are embedded within a nonparametric Bayesian setup. Handling such a model is not probabilistically straightforward as the…

Methodology · Statistics 2016-01-14 Luke Bornn , Neil Shephard , Reza Solgi

We show how to achieve the notion of "multicalibration" from H\'ebert-Johnson et al. [2018] not just for means, but also for variances and other higher moments. Informally, it means that we can find regression functions which, given a data…

Machine Learning · Computer Science 2020-08-19 Christopher Jung , Changhwa Lee , Mallesh M. Pai , Aaron Roth , Rakesh Vohra

We find necessary and sufficient conditions for the existence of a probability measure on $\mathbb{N}_0$, the nonnegative integers, whose first $n$ moments are a given $n$-tuple of nonnegative real numbers. The results, based on finding an…

Probability · Mathematics 2021-08-16 M. Infusino , T. Kuna , J. L. Lebowitz , E. R. Speer

Let $\mu$ be a given Borel measure on $\K\subseteq\R^n$ and let $y=(y_\alpha)$, $\alpha\in\N^n$, be a given sequence. We provide several conditions linking $y$ and the moment sequence $z=(z_\alpha)$ of $\mu$, for $y$ to be the moment…

Functional Analysis · Mathematics 2011-11-09 Jean B. Lasserre

We consider the "moment vanishing problem" for a general class of piecewise-analytic functions which satisfy on each continuity interval a linear ODE with polynomial coefficients. This problem, which essentially asks how many zero first…

Classical Analysis and ODEs · Mathematics 2013-02-06 Dmitry Batenkov , Gal Binyamini

We obtain the best possible upper bounds for the moments of a single order statistic from independent, non-negative random variables, in terms of the population mean. The main result covers the independent identically distributed case.…

Statistics Theory · Mathematics 2018-06-14 Nickos Papadatos

This paper proposes a linear categorical random coefficient model, in which the random coefficients follow parametric categorical distributions. The distributional parameters are identified based on a linear recurrence structure of moments…

Econometrics · Economics 2023-03-01 Zhan Gao , M. Hashem Pesaran