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We study truncated moment sequences of distribution mixtures, especially from Gaussian and log-normal distributions and their Carath\'eodory numbers. For $\mathsf{A} = \{a_1,\dots,a_m\}$ continuous (sufficiently differentiable) functions on…

Probability · Mathematics 2019-07-01 Philipp J. di Dio

Gaussian mixture models (GMMs) are fundamental tools in statistical and data sciences. We study the moments of multivariate Gaussians and GMMs. The $d$-th moment of an $n$-dimensional random variable is a symmetric $d$-way tensor of size…

Machine Learning · Statistics 2022-03-23 João M. Pereira , Joe Kileel , Tamara G. Kolda

In measure theory several results are known how measure spaces are transformed into each other. But since moment functionals are represented by a measure we investigate in this study the effects and implications of these measure…

Functional Analysis · Mathematics 2020-07-28 Philipp J. di Dio

In this paper we improve the bounds for the Carath\'eodory number, especially on algebraic varieties and with small gaps (not all monomials are present). We provide explicit lower and upper bounds on algebraic varieties, $\mathbb{R}^n$, and…

Functional Analysis · Mathematics 2021-07-20 Philipp J. di Dio , Mario Kummer

The problem of recovering a moment-determinate multivariate function $f$ via its moment sequence is studied. Under mild conditions on $f$, the point-wise and $L_1$-rates of convergence for the proposed constructions are established. The…

Statistics Theory · Mathematics 2023-12-08 Robert Mnatsakanov , Rafik Aramyan , Farhad Jafari

Gaussian mixture models are universal approximators in the sense that any smooth density can be approximated arbitrarily well with a Gaussian mixture model with enough components. Due to their broad expressive power, Gaussian mixture models…

Computation · Statistics 2025-02-12 Haley Colgate Kottler , Julia Lindberg , Jose Israel Rodriguez

The Method of Moments [Pea94] is one of the most widely used methods in statistics for parameter estimation, by means of solving the system of equations that match the population and estimated moments. However, in practice and especially…

Statistics Theory · Mathematics 2019-04-16 Yihong Wu , Pengkun Yang

This survey provides a unified discussion of multiple integrals, moments, cumulants and diagram formulae associated with functionals of completely random measures. Our approach is combinatorial, as it is based on the algebraic formalism of…

Probability · Mathematics 2008-11-12 Giovanni Peccati , Murad S. Taqqu

Let $\lambda(n)$ be the Liouville function. We study the distribution of \[ \frac{1}{x^{1/2}}\sum_{x\leq n\leq 2x}\lambda(f(n)) \] over random polynomials $f$ of fixed degree $d$ and coefficients bounded in magnitude by $H$. In particular…

Number Theory · Mathematics 2024-08-21 Cameron Wilson

We consider the inverse problem for the polynomial map which sends an $m$-tuple of quadratic forms in $n$ variables to the sum of their $d$-th powers. This map captures the moment problem for mixtures of $m$ centered $n$-variate Gaussians.…

Algebraic Geometry · Mathematics 2026-02-23 Alexander Taveira Blomenhofer , Alex Casarotti , Alessandro Oneto , Mateusz Michałek

Since Pearson [Philosophical Transactions of the Royal Society of London. A, 185 (1894), pp. 71-110] first applied the method of moments (MM) for modeling data as a mixture of one-dimensional Gaussians, moment-based estimation methods have…

Machine Learning · Computer Science 2025-07-29 Liu Zhang , Oscar Mickelin , Sheng Xu , Amit Singer

We consider the problem of finding a (non-negative) measure $\mu$ on $\mathfrak{B}(\mathbb{C}^n)$ such that $\int_{\mathbb{C}^n} \mathbf{z}^{\mathbf{k}} d\mu(\mathbf{z}) = s_{\mathbf{k}}$, $\forall \mathbf{k}\in\mathcal{K}$. Here…

Functional Analysis · Mathematics 2021-02-12 Sergey M. Zagorodnyuk

We derive a Gaussian approximation result for the maximum of a sum of random vectors under $(2+\iota)$-th moments. Our main theorem is abstract and nonasymptotic, and can be applied to a variety of statistical learning problems. The proof…

Statistics Theory · Mathematics 2019-05-28 Qiang Sun

The first part of this paper is devoted to an analysis of moment problems in R^n with supports contained in a closed set defined by finitely many polynomial inequalities. The second part of the paper uses the representation results of…

Classical Analysis and ODEs · Mathematics 2016-09-07 Mihai Putinar , Florian-Horia Vasilescu

The points of a moment variety are the vectors of all moments up to some order of a family of probability distributions. We study this variety for mixtures of Gaussians. Following up on Pearson's classical work from 1894, we apply current…

Algebraic Geometry · Mathematics 2017-04-06 Carlos Améndola , Jean-Charles Faugère , Bernd Sturmfels

We characterize the existence of the $L^1$ solutions of the truncated moments problem in several real variables on unbounded supports by the existence of the maximum of certain concave Lagrangian functions. A natural regularity assumption…

Functional Analysis · Mathematics 2012-09-04 Calin-Grigore Ambrozie

This paper is about the moment problem on a finite-dimensional vector space of continuous functions. We investigate the structure of the convex cone of moment functionals (supporting hyperplanes, exposed faces, inner points) and treat…

Functional Analysis · Mathematics 2018-04-20 Philipp J. di Dio , Konrad Schmüdgen

We provide a necessary and sufficient condition for the representability of a function as the classical multidimensional Laplace transform, when the support of the representing measure is contained in some generalized semi-algebraic set.…

Functional Analysis · Mathematics 2012-02-08 Ami Viselter

We compute an asymptotic formula for the mixed second moment of the $\mu$-th and $\nu$-th derivatives of quadratic Dirichlet $L$-functions over monic, irreducible polynomials in the function field setting.

Number Theory · Mathematics 2024-12-03 Christopher G. Best

The method of moments is a classical statistical technique for density estimation that solves a system of moment equations to estimate the parameters of an unknown distribution. A fundamental question critical to understanding…

Methodology · Statistics 2024-06-12 Julia Lindberg , Carlos Améndola , Jose Israel Rodriguez
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