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We prove oracle inequalities for a penalized log-likelihood criterion that hold even if the data are not independent and not stationary, based on a martingale approach. The assumptions are checked for various contexts: density estimation…

Statistics Theory · Mathematics 2024-05-20 Julien Aubert , Luc Lehéricy , Patricia Reynaud-Bouret

We introduce an iterative discrete information production process where we can extend ordered normalised vectors by new elements based on a simple affine transformation, while preserving the predefined level of inequality, G, as measured by…

Physics and Society · Physics 2024-01-17 Lucio Bertoli-Barsotti , Marek Gagolewski , Grzegorz Siudem , Barbara Żogała-Siudem

The large-sample properties of likelihood-based statistical inference under mixture models have received much attention from statisticians. Although the consistency of the nonparametric MLE is regarded as a standard conclusion, many…

Statistics Theory · Mathematics 2016-07-06 Jiahua Chen

We study the law of the iterated logarithm (LIL) for the maximum likelihood estimation of the parameters (as a convex optimization problem) in the generalized linear models with independent or weakly dependent ($\rho$-mixing, $m$-dependent)…

Statistics Theory · Mathematics 2020-04-28 Xiaowei Yang , Shuang Song , Huiming Zhang

Graded posets frequently arise throughout combinatorics, where it is natural to try to count the number of elements of a fixed rank. These counting problems are often $\#\textbf{P}$-complete, so we consider approximation algorithms for…

Data Structures and Algorithms · Computer Science 2023-04-11 Prateek Bhakta , Ben Cousins , Matthew Fahrbach , Dana Randall

The chaotic nature of fluid flow and the uncertainties in initial conditions limit predictability. Small errors that occur in the initial condition can grow exponentially until they saturate at $\mathcal{O}$(1). Ensemble forecasting…

Numerical Analysis · Mathematics 2024-07-16 Rui Fang

We consider ordered logit models for directed network data that allow for flexible sender and receiver fixed effects that can vary arbitrarily across outcome categories. This structure poses a significant incidental parameter problem,…

Econometrics · Economics 2025-07-23 Chris Muris , Cavit Pakel , Qichen Zhang

In this paper, we study stochastic ordering results between two finite mixtures with single and multiple outliers, assuming subpopulations follow general exponentiated location-scale distributions. For single-outlier mixtures, several…

Statistics Theory · Mathematics 2025-11-04 Raju Bhakta , Kaushik Gupta , Ghobad Saadat Kia , Suchandan Kayal

This paper studies least-square regression penalized with partly smooth convex regularizers. This class of functions is very large and versatile allowing to promote solutions conforming to some notion of low-complexity. Indeed, they force…

Optimization and Control · Mathematics 2014-07-01 Samuel Vaiter , Gabriel Peyré , Jalal M. Fadili

Regression by composition provides a flexible framework for constructing conditional distributions through sequential group actions. However, when multiple flows act on the same distribution, the model becomes non-identifiable, leading to…

Methodology · Statistics 2026-03-30 Safaa K. Kadhem

The matrix completion problem consists in reconstructing a matrix from a sample of entries, possibly observed with noise. A popular class of estimator, known as nuclear norm penalized estimators, are based on minimizing the sum of a data…

Statistics Theory · Mathematics 2015-04-21 Jean Lafond

Several interesting models for contingency tables are defined by a system of equality and inequality constraints on a suitable set of marginal log-linear parameters. After reviewing the most common difficulties which are intrinsic to order…

Statistics Theory · Mathematics 2014-01-09 Roberto Colombi , Antonio Forcina

The problem of finding the maximum likelihood estimates for the regression coefficients in generalised linear models with an L1 sparsity penalty is shown to be equivalent to minimising the unpenalised maximum log-likelihood function over a…

Methodology · Statistics 2015-12-21 Tom Michoel

We study the problem of modeling univariate distributions via their quantile functions. We introduce a flexible family of distributions whose quantile function is a linear combination of basis quantiles. Because the model is linear in its…

Methodology · Statistics 2026-02-05 Cheng Peng , Yizhou Li , Stan Uryasev

We investigate the race between prime numbers in many residue classes modulo $q$, assuming the standard conjectures GRH and LI. Among our results we exhibit, for the first time, prime races modulo $q$ with $n$ competitor classes where the…

Number Theory · Mathematics 2015-09-25 Adam J. Harper , Youness Lamzouri

This paper investigates correct variable selection in finite samples via $\ell_1$ and $\ell_1+\ell_2$ type penalization schemes. The asymptotic consistency of variable selection immediately follows from this analysis. We focus on logistic…

Statistics Theory · Mathematics 2008-12-16 Florentina Bunea

In this paper, we first determine the minimum possible size of an Fq-linear set of rank k in PG(1, q^n). We obtain this result by relating it to the number of directions determined by a linearized polynomial whose domain is restricted to a…

Combinatorics · Mathematics 2018-04-23 Jan De Beule , Geertrui Van de Voorde

When some treatments are ordered according to the categories of an ordinal categorical variable (e.g., extent of side effects) in a monotone order, one might be interested in knowing wether the treatments are equally effective or not. One…

Methodology · Statistics 2014-02-24 Nirian Martín , Raquel Mata , Leandro Pardo

Suppose that we observe entries or, more generally, linear combinations of entries of an unknown $m\times T$-matrix $A$ corrupted by noise. We are particularly interested in the high-dimensional setting where the number $mT$ of unknown…

Statistics Theory · Mathematics 2011-05-16 Angelika Rohde , Alexandre B. Tsybakov

This paper studies the complexity of estimating Renyi divergences of discrete distributions: $p$ observed from samples and the baseline distribution $q$ known \emph{a priori}. Extending the results of Acharya et al. (SODA'15) on estimating…

Information Theory · Computer Science 2017-02-09 Maciej Skorski