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We consider a robust version of the classical Wald test statistics for testing simple and composite null hypotheses for general parametric models. These test statistics are based on the minimum density power divergence estimators instead of…

Statistics Theory · Mathematics 2016-07-04 Abhik Ghosh , Abhijit Mandal , Nirian Martin , Leandro Pardo

Robust estimators and Wald-type tests are developed for the multinomial logistic regression based on $\phi$-divergence measures. The robustness of the proposed estimators and tests is proved through the study of their influence functions…

Statistics Theory · Mathematics 2021-02-08 Elena Castilla , Pedro J. Chocano

We study the properties of several likelihood-based statistics commonly used in testing for the presence of a known signal under a mixture model with known background, but unknown signal fraction. Under the null hypothesis of no signal, all…

Data Analysis, Statistics and Probability · Physics 2018-12-26 Igor Volobouev , A. Alexandre Trindade

The Wald test remains ubiquitous in statistical practice despite shortcomings such as its inaccuracy in small samples and lack of invariance under reparameterization. This paper develops on another but lesser-known shortcoming called the…

Methodology · Statistics 2022-09-15 Thomas William Yee

Random-matrix theory is applied to transition-rate matrices in the Pauli master equation. We study the distribution and correlations of eigenvalues, which govern the dynamics of complex stochastic systems. Both the cases of identical and of…

Statistical Mechanics · Physics 2013-05-29 Carsten Timm

A sum of a large-dimensional random matrix polynomial and a fixed low-rank matrix polynomial is considered. The main assumption is that the resolvent of the random polynomial converges to some deterministic limit. A formula for the limit of…

Probability · Mathematics 2022-05-23 Patryk Pagacz , Michał Wojtylak

With advancement of medicine, alternative exposures or interventions are emerging with respect to a common outcome, and there are needs to formally test the difference in the associations of multiple exposures. We propose a duplication…

Methodology · Statistics 2024-12-04 Rikuta Hamaya , Peilu Wang , Lin Ge , Edward L. Giovannucci , Molin Wang

In this note, convergence of random variables will be revisited. We will give the answers to 5 questions among the 6 open questions introduced in (Convergence rates in the law of large numbers and new kinds of convergence of random…

Probability · Mathematics 2020-04-07 Ze-Chun Hu , Ting Ma , Xiu-Ju Zhu

In this paper, a new and convenient $\chi^2$ wald test based on MCMC outputs is proposed for hypothesis testing. The new statistic can be explained as MCMC version of Wald test and has several important advantages that make it very…

Econometrics · Economics 2018-01-04 Yong Li , Xiaobin Liu , Jun Yu , Tao Zeng

In this short note a differential version of the classical Weil descent is established in all characteristics. This yields a ready-to-deploy tool of differential restriction of scalars for differential varieties over finite differential…

Algebraic Geometry · Mathematics 2020-03-09 Omar León Sánchez , Marcus Tressl

In the first part of these notes, we review some of the recent developments in the study of the spectral properties of Wigner matrices. In the second part, we present a new proof of a Wegner estimate for the eigenvalues of a large class of…

Mathematical Physics · Physics 2011-03-09 Anna Maltsev , Benjamin Schlein

In this note, a Wegner estimate for random divergence-type operators that are monotone in the randomness is proven. The proof is based on a recently shown unique continuation estimate for the gradient and the ensuing eigenvalue liftings.…

Mathematical Physics · Physics 2021-06-22 Alexander Dicke

Intraclass correlation in bilateral data has been investigated in recent decades with various statistical methods. In practice, stratifying bilateral data by some control variables will provide more sophisticated statistical results to…

Methodology · Statistics 2023-03-24 Wanqing Tian , Chang-Xing Ma

A short note on bounds on distance to variety of a point in terms of the Taylor coefficients at the point.

Complex Variables · Mathematics 2017-01-31 Vikram Sharma

Relying on recent advances in statistical estimation of covariance distances based on random matrix theory, this article proposes an improved covariance and precision matrix estimation for a wide family of metrics. The method is shown to…

Machine Learning · Statistics 2021-02-03 Malik Tiomoko , Florent Bouchard , Guillaume Ginholac , Romain Couillet

We analyze complex networks under random matrix theory framework. Particularly, we show that $\Delta_3$ statistic, which gives information about the long range correlations among eigenvalues, provides a qualitative measure of randomness in…

Statistical Mechanics · Physics 2015-05-13 Sarika Jalan , Jayendra N. Bandyopadhyay

Every sufficiently big matrix with small spectral norm has a nearby low-rank matrix if the distance is measured in the maximum norm (Udell & Townsend, SIAM J Math Data Sci, 2019). We use the Hanson--Wright inequality to improve the estimate…

Numerical Analysis · Mathematics 2025-04-09 Stanislav Budzinskiy

In this note, we study the relationship between the variational gap and the variance of the (log) likelihood ratio. We show that the gap can be upper bounded by some form of dispersion measure of the likelihood ratio, which suggests the…

Machine Learning · Computer Science 2019-06-11 Chin-Wei Huang , Aaron Courville

We discuss some extensions and refinements of the variance bounds for both real and complex numbers. The related bounds for the eigenvalues and spread of a matrix are also derived here.

Functional Analysis · Mathematics 2019-05-21 R. Sharma , A. Sharma , R. Saini

A novel method is proposed for detecting changes in the covariance structure of moderate dimensional time series. This non-linear test statistic has a number of useful properties. Most importantly, it is independent of the underlying…

Methodology · Statistics 2021-08-18 Sean Ryan , Rebecca Killick