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Inference based on the penalized density ratio model is proposed and studied. The model under consideration is specified by assuming that the log--likelihood function of two unknown densities is of some parametric form. The model has been…

Statistics Theory · Mathematics 2008-07-17 Konstantinos Fokianos

In this article we recover the distribution function (and possible density) of an arbitrary random variable that is subject to an additive measurement error. This problem is also known as deconvolution and has a long tradition in…

Statistics Theory · Mathematics 2025-10-07 Henrik Kaiser

Given samples from an unknown distribution $p$, is it possible to distinguish whether $p$ belongs to some class of distributions $\mathcal{C}$ versus $p$ being far from every distribution in $\mathcal{C}$? This fundamental question has…

Data Structures and Algorithms · Computer Science 2015-12-09 Jayadev Acharya , Constantinos Daskalakis , Gautam Kamath

In this work we develop a scalable computational framework for the solution of PDE-constrained optimal control under high-dimensional uncertainty. Specifically, we consider a mean-variance formulation of the control objective and employ a…

Optimization and Control · Mathematics 2019-03-27 Peng Chen , Umberto Villa , Omar Ghattas

We consider the estimation of the total number $N$ of species based on the abundances of species that have been observed. We adopt a non parametric approach where the true abundance distribution $p$ is only supposed to be convex. From this…

Methodology · Statistics 2014-04-21 Cécile Durot , Sylvie Huet , François Koladjo , Stéphane Robin

In this paper, we prove strong consistency of an estimator by the truncated singular value decomposition for a multivariate errors-in-variables linear regression model with collinearity. This result is an extension of Gleser's proof of the…

Statistics Theory · Mathematics 2026-02-11 Kensuke Aishima

We introduce the first analytical model of asymmetric community dynamics to yield Hubbell's neutral theory in the limit of functional equivalence among all species. Our focus centers on an asymmetric extension of Hubbell's local community…

Populations and Evolution · Quantitative Biology 2010-12-06 Andrew E. Noble , Nico M. Temme , William F. Fagan , Timothy H. Keitt

Recently some papers, such as Aban, Meerschaert and Panorska (2006), Nuyts (2010) and Clark (2013), have drawn attention to possible truncation in Pareto tail modelling. Sometimes natural upper bounds exist that truncate the probability…

Statistics Theory · Mathematics 2015-05-21 Jan Beirlant , Isabel Fraga Alves , Ivette Gomes

Let $\{Z_k\}_{k\geqslant 1}$ denote a sequence of independent Bernoulli random variables defined by ${\mathbb P}(Z_k=1)=1/k=1-{\mathbb P}(Z_k=0)$ $(k\geqslant 1)$ and put $T_n:=\sum_{1\leqslant k\leqslant n}kZ_k$. It is then known that…

Probability · Mathematics 2021-03-09 Régis de la Bretèche , Gérald Tenenbaum

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

Given a certain invariant random matrix ensemble characterised by the joint probability distribution of eigenvalues $P(\lambda_1,\ldots,\lambda_N)$, many important questions have been related to the study of linear statistics of eigenvalues…

Statistical Mechanics · Physics 2018-05-17 Aurélien Grabsch , Satya N. Majumdar , Christophe Texier

We study the almost sure convergence of randomly truncated stochastic algorithms. We present a new convergence theorem which extends the already known results by making vanish the classical condition on the noise terms. The aim of this work…

Probability · Mathematics 2009-06-29 Jérôme Lelong

This paper studies the sample complexity of searching over multiple populations. We consider a large number of populations, each corresponding to either distribution P0 or P1. The goal of the search problem studied here is to find one…

Information Theory · Computer Science 2016-11-17 Matthew L. Malloy , Gongguo Tang , Robert D. Nowak

The analysis of a truncated sample can be hindered by censoring. Survival information may be lost to follow-up or the birthdate may be missing. The data can still be modeled as a truncated point process and it is close to a Poisson process,…

Methodology · Statistics 2025-08-12 Fiete Sieg , Anne-Marie Toparkus , Rafael Weissbach

Sampling theory has benefited from a surge of research in recent years, due in part to the intense research in wavelet theory and the connections made between the two fields. In this survey we present several extensions of the Shannon…

Information Theory · Computer Science 2008-12-17 Y. C. Eldar , T. Michaeli

Reviewing the semiclassical theory for the parametric level density fluctuations, we show that for large parametric changes the density correlation function, after rescaling, becomes universal and coincides with the leading asymptotic term…

Discrete sampling theorem is formulated that refers to discrete signals specified by a finite number of their samples and band-limited in a domain of a certain orthogonal transform. Conditions of the recoverability of such signals from…

Optics · Physics 2009-02-24 L. Yaroslavsky

We consider the problem of drawing samples from posterior distributions formed under a Dirichlet prior and a truncated multinomial likelihood, by which we mean a Multinomial likelihood function where we condition on one or more counts being…

Methodology · Statistics 2012-09-04 Matthew James Johnson , Alan S. Willsky

We extend the classical fundamental theorem of the local theory of smooth curves to a wider class of non-smooth data. Curvature and torsion are prescribed in terms of the distributional derivative measures of two given functions of bounded…

Differential Geometry · Mathematics 2025-06-17 Domenico Mucci , Alberto Saracco

Stochastic processes wherein the size of the state space is changing as a function of time offer models for the emergence of scale-invariant features observed in complex systems. I consider such a sample-space reducing (SSR) stochastic…

Statistical Mechanics · Physics 2016-05-04 Avinash Chand Yadav
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