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We show an explicit formula, with a quite easy deduction, for the exponential matrix $e^{tA}$ of a real square matrix $A$ of order $n\times n$. The elementary method developed requires neither Jordan canonical form, nor eigenvectors, nor…

Classical Analysis and ODEs · Mathematics 2022-02-15 Oswaldo Rio Branco de Oliveira

We consider tests of hypotheses when the parameters are not identifiable under the null in semiparametric models, where regularity conditions for profile likelihood theory fail. Exponential average tests based on integrated profile…

Statistics Theory · Mathematics 2009-08-25 Rui Song , Michael R. Kosorok , Jason P. Fine

This thesis studies high-dimensional, continuous-valued pairwise Markov Random Fields. We are particularly interested in approximating pairwise densities whose logarithm belongs to a Sobolev space. For this problem we propose the method of…

Statistics Theory · Mathematics 2015-06-12 Eric Janofsky

Exponential distributions appear in a wide range of applications including chemistry, nuclear physics, time series analyses, and stock market trends. There are conceivable circumstances in which one would be interested in the cumulative…

History and Overview · Mathematics 2018-03-23 Cecilia Chirenti , M. Coleman Miller

In this paper, we derive closed-form estimators for the parameters of certain exponential family distributions through the maximum a posteriori (MAP) equations. A Monte Carlo simulation is conducted to assess the performance of the proposed…

Methodology · Statistics 2025-05-16 Roberto Vila , Helton Saulo , Eduardo Nakano

Simultaneously testing $K$ hypotheses while controlling the family-wise error rate is a fundamental problem in statistics. Existing procedures (Bonferroni, Holm, Hochberg, Hommel) provide valid control but sacrifice power, increasingly so…

Methodology · Statistics 2026-04-14 Prasanjit Dubey , Xiaoming Huo

The present paper is a continuation of the author's previous works, in which necessary and sufficient local extrema at a stationary point of a polynomial or a power series (and thus of an analytic function) are given. It is known that for…

Optimization and Control · Mathematics 2024-02-29 V. N. Nefedov

We propose a new class of extreme-value copulas which are extreme-value limits of conditional normal models. Conditional normal models are generalizations of conditional independence models, where the dependence among observed variables is…

Methodology · Statistics 2021-02-16 Pavel Krupskii , Marc G. Genton

On a locally compact group $E$ with countable base, we consider a random walk $X$ that has a unique (up to a positive factor) $r$-invariant measure for some $r>0$. Under some weak conditions on the measure, there is a unique continuous…

Probability · Mathematics 2015-11-10 M. G. Shur

The closure of a discrete exponential family is described by a finite set of equations corresponding to the circuits of an underlying oriented matroid. These equations are similar to the equations used in algebraic statistics, although they…

Statistics Theory · Mathematics 2011-09-19 Johannes Rauh , Thomas Kahle , Nihat Ay

Variational inference for latent variable models is prevalent in various machine learning problems, typically solved by maximizing the Evidence Lower Bound (ELBO) of the true data likelihood with respect to a variational distribution.…

Machine Learning · Computer Science 2018-07-11 Guoqing Zheng , Yiming Yang , Jaime Carbonell

A new empirical Bayes approach to variable selection in the context of generalized linear models is developed. The proposed algorithm scales to situations in which the number of putative explanatory variables is very large, possibly much…

Methodology · Statistics 2021-06-29 Haim Bar , James Booth , Martin T. Wells

Prior work applying semiparametric theory to causal inference has primarily focused on deriving estimators that exhibit statistical robustness under a prespecified causal model that permits identification of a desired causal parameter.…

Methodology · Statistics 2024-07-02 Junhui Yang , Rohit Bhattacharya , Youjin Lee , Ted Westling

This paper investigates a statistical procedure for testing the equality of two independent estimated covariance matrices when the number of potentially dependent data vectors is large and proportional to the size of the vectors, that is,…

Statistics Theory · Mathematics 2020-03-09 Rémy Mariétan , Stephan Morgenthaler

Evidence Networks can enable Bayesian model comparison when state-of-the-art methods (e.g. nested sampling) fail and even when likelihoods or priors are intractable or unknown. Bayesian model comparison, i.e. the computation of Bayes…

Machine Learning · Computer Science 2024-01-11 Niall Jeffrey , Benjamin D. Wandelt

Considered here is a hypothesis test for the coefficients in the change-plane regression models to detect the existence of a change plane. The test that is considered is from the class of test problems in which some parameters are not…

Statistics Theory · Mathematics 2024-08-02 Xu Liu , Jian Huang , Yong Zhou , Feipeng Zhang , Panpan Ren

We consider the segmentation problem of univariate distributions from the exponential family with multiple parameters. In segmentation, the choice of the number of segments remains a difficult issue due to the discrete nature of the…

Statistics Theory · Mathematics 2015-03-27 Alice Cleynen , Emilie Lebarbier

The sum of independent, but not necessary identically distributed, exponential random variables follows hypoexponential distribution. We focus on a particular case when all, but one rate parameters of the exponential variables are…

Probability · Mathematics 2023-04-04 George Yanev

The article is devoted to the study of exponential statistical structures of type B, which constitute a subclass of exponential families of probability distributions. This class is characterized by a number of analytical and probabilistic…

Statistics Theory · Mathematics 2025-12-23 Oleksandr Volkov , Yurii Volkov

This paper introduces e-fold cross-validation, an energy-efficient alternative to k-fold cross-validation. It dynamically adjusts the number of folds based on a stopping criterion. The criterion checks after each fold whether the standard…

Machine Learning · Computer Science 2024-10-29 Christopher Mahlich , Tobias Vente , Joeran Beel