English
Related papers

Related papers: Asymptotics of higher criticism via Gaussian appro…

200 papers

The performance of Bayesian detection of Gaussian signals using noisy observations is investigated via the error exponent for the average error probability. Under unknown signal correlation structure or limited processing capability it is…

Information Theory · Computer Science 2009-11-11 Youngchul Sung , Lang Tong , H. Vincent Poor

Sampling from various kinds of distributions is an issue of paramount importance in statistics since it is often the key ingredient for constructing estimators, test procedures or confidence intervals. In many situations, the exact sampling…

Statistics Theory · Mathematics 2018-11-05 Avetik Karagulyan

We consider the problem of finding, for a given quadratic measure of non-uniformity of a set of $N$ points (such as $L_2$ star-discrepancy or diaphony), the asymptotic distribution of this discrepancy for truly random points in the limit…

Computational Physics · Physics 2009-10-30 Andre van Hameren , Ronald Kleiss , Jiri Hoogland

Recent years have seen tremendous advances in the theory and application of sequential experiments. While these experiments are not always designed with hypothesis testing in mind, researchers may still be interested in performing tests…

Econometrics · Economics 2023-06-29 Karun Adusumilli

The Peaks Over Threshold (POT) method is the most popular statistical method for the analysis of univariate extremes. Even though there is a rich applied literature on Bayesian inference for the POT, the asymptotic theory for such proposals…

Statistics Theory · Mathematics 2025-04-01 Clément Dombry , Simone A. Padoan , Stefano Rizzelli

Variational inference is a general framework to obtain approximations to the posterior distribution in a Bayesian context. In essence, variational inference entails an optimization over a given family of probability distributions to choose…

Statistics Theory · Mathematics 2025-07-24 Janis Keck

We make use of the empirical process theory to approximate the adapted Hill estimator, for censored data, in terms of Gaussian processes. Then, we derive its asymptotic normality, only under the usual second-order condition of regular…

Statistics Theory · Mathematics 2015-07-07 Brahim Brahimi , Djamel Meraghni , Abdelhakim Necir

The article is devoted to the nonparametric estimation of the quadratic covariation of non-synchronously observed It\^o processes in an additive microstructure noise model. In a high-frequency setting, we aim at establishing an asymptotic…

Statistics Theory · Mathematics 2011-06-22 Markus Bibinger

We consider a classical risk process with arrival of claims following a non-stationary Hawkes process. We study the asymptotic regime when the premium rate and the baseline intensity of the claims arrival process are large, and claim size…

Risk Management · Quantitative Finance 2019-08-22 Zailei Cheng , Youngsoo Seol

We consider the problems of confidence estimation and hypothesis testing on a parameter of signal observed in Gaussian white noise. For these problems we point out lower bounds of asymptotic efficiency in the zone of moderate deviation…

Statistics Theory · Mathematics 2015-01-27 Mikhail Ermakov

This paper introduces a quasi-likelihood ratio testing procedure for diffusion processes observed under nonsynchronous sampling schemes. High-frequency data, particularly in financial econometrics, are often recorded at irregular time…

Statistics Theory · Mathematics 2025-03-25 Teppei Ogihara , Futo Ueno

The Gaussian graphical model, a popular paradigm for studying relationship among variables in a wide range of applications, has attracted great attention in recent years. This paper considers a fundamental question: When is it possible to…

Statistics Theory · Mathematics 2015-06-04 Zhao Ren , Tingni Sun , Cun-Hui Zhang , Harrison H. Zhou

Score matching is an estimation procedure that has been developed for statistical models whose probability density function is known up to proportionality but whose normalizing constant is intractable, so that maximum likelihood is…

Methodology · Statistics 2024-04-23 Jiazhen Xu , Janice L. Scealy , Andrew T. A. Wood , Tao Zou

Distance correlation has become an increasingly popular tool for detecting the nonlinear dependence between a pair of potentially high-dimensional random vectors. Most existing works have explored its asymptotic distributions under the null…

Statistics Theory · Mathematics 2021-10-06 Lan Gao , Yingying Fan , Jinchi Lv , Qi-Man Shao

This paper is concerned with testing normality in a Hilbert space based on the maximum mean discrepancy. Specifically, we discuss the behavior of the test from two standpoints: asymptotics and practical aspects. Asymptotic normality of the…

Statistics Theory · Mathematics 2019-02-12 Natsumi Makigusa , Kanta Naito

Two new test statistics are introduced to test the null hypotheses that the sampling distribution has an increasing hazard rate on a specified interval [0,a]. These statistics are empirical L_1-type distances between the isotonic estimates,…

Statistics Theory · Mathematics 2015-03-17 Piet Groeneboom , Geurt Jongbloed

In this paper, our interest is in the problem of simultaneous hypothesis testing when the test statistics corresponding to the individual hypotheses are possibly correlated. Specifically, we consider the case when the test statistics…

Statistics Theory · Mathematics 2019-01-14 Anupam Kundu , Subir Kumar Bhandari

Consider a multiple hypothesis testing setting involving rare/weak effects: relatively few tests, out of possibly many, deviate from their null hypothesis behavior. Summarizing the significance of each test by a P-value, we construct a…

Statistics Theory · Mathematics 2021-10-20 David L. Donoho , Alon Kipnis

Numerical and analytical results are presented for the maximal relative height distribution of stationary periodic Gaussian signals (one dimensional interfaces) displaying a 1/f^alpha power spectrum. For 0<alpha<1 (regime of decaying…

Statistical Mechanics · Physics 2013-05-29 G. Gyorgyi , N. R. Moloney , K. Ozogany , Z. Racz

Motivated by real-world machine learning applications, we analyze approximations to the non-asymptotic fundamental limits of statistical classification. In the binary version of this problem, given two training sequences generated according…

Information Theory · Computer Science 2018-12-07 Lin Zhou , Vincent Y. F. Tan , Mehul Motani