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We derive a new discrepancy statistic for measuring differences between two probability distributions based on combining Stein's identity with the reproducing kernel Hilbert space theory. We apply our result to test how well a probabilistic…

Machine Learning · Statistics 2016-07-04 Qiang Liu , Jason D. Lee , Michael I. Jordan

Hypothesis testing results often rely on simple, yet important assumptions about the behaviour of the distribution of p-values under the null and the alternative. We examine tests for one dimensional parameters of interest that converge to…

Statistics Theory · Mathematics 2021-08-06 Yanbo Tang , Radu Craiu , Lei Sun

Several approaches to testing the hypothesis that two histograms are drawn from the same distribution are investigated. We note that single-sample continuous distribution tests may be adapted to this two-sample grouped data situation. The…

Data Analysis, Statistics and Probability · Physics 2008-04-03 Frank C. Porter

The log-normal distribution is used to describe the positive data, that it has skewed distribution with small mean and large variance. This distribution has application in many sciences for example medicine, economics, biology and…

Methodology · Statistics 2015-08-10 Saba Aghadoust , Kamel Abdollahnezhad , Farhad Yaghmaei , Ali Akbar Jafari

We consider the problem of goodness-of-fit testing for a model that has at least one unknown parameter that cannot be eliminated by transformation. Examples of such problems can be as simple as testing whether a sample consists of…

Methodology · Statistics 2021-04-28 Sean van der Merwe

Testing for the significance of a subset of regression coefficients in a linear model, a staple of statistical analysis, goes back at least to the work of Fisher who introduced the analysis of variance (ANOVA). We study this problem under…

Statistics Theory · Mathematics 2012-02-24 Ery Arias-Castro , Emmanuel J. Candès , Yaniv Plan

We consider testing zero pricing errors in high-dimensional linear factor pricing models. Existing methods are mainly based on either an $L_2$ statistic, which is effective under dense alternatives, or an $L_\infty$ statistic, which is…

Methodology · Statistics 2026-04-01 Ping Zhao , Huifang Ma , Long Feng

In this work, we revisit the one- and two-sample testing problems: binary hypothesis testing in which one or both distributions are unknown. For the one-sample test, we provide a more streamlined proof of the asymptotic optimality of…

Information Theory · Computer Science 2026-04-21 Arick Grootveld , Biao Chen , Venkata Gandikota

While there exists several inferential methods for analyzing functional data in factorial designs, there is a lack of statistical tests that are valid (i) in general designs, (ii) under non-restrictive assumptions on the data generating…

Methodology · Statistics 2023-06-28 Merle Munko , Marc Ditzhaus , Markus Pauly , Łukasz Smaga , Jin-Ting Zhang

The generalized likelihood ratio (GLR) test proposed by Fan, Zhang and Zhang [Ann. Statist. 29 (2001) 153-193] and Fan and Yao [Nonlinear Time Series: Nonparametric and Parametric Methods (2003) Springer] is a generally applicable…

Statistics Theory · Mathematics 2013-06-21 Yongmiao Hong , Yoon-Jin Lee

In this paper, we have obtained conditions on parameters that result in dispersive ordering and star ordering among two unequal sets of random variables from Proportional hazard rate and Proportional reversed hazard rate family of…

Statistics Theory · Mathematics 2020-03-02 Madhurima Datta , Nitin Gupta

This paper studies estimation of and inference on a distribution function $F$ that is concave on the nonnegative half line and admits a density function $f$ with potentially unbounded support. When $F$ is strictly concave, we show that the…

Statistics Theory · Mathematics 2019-11-12 Zheng Fang

The two-sample problem for Cronbach's coefficient $\alpha_C$, as an estimate of test or composite score reliability, has attracted little attention, compared to the extensive treatment of the one-sample case. It is necessary to compare the…

Statistics Theory · Mathematics 2017-06-20 Markus Pauly , Maria Umlauft , Ali Ünlü

In this paper, we consider functionals of the form $H_\alpha(u)=F(u)+\alpha G(u)$ with $\alpha\in[0,+\infty)$, where $u$ varies in a set $U\neq\emptyset$ (without further structure). We first revisit a result stating that, excluding at most…

Optimization and Control · Mathematics 2025-01-28 Massimo Fornasier , Jona Klemenc , Alessandro Scagliotti

In this article, we give an overview of our project on higher-order program verification based on HFL (higher-order fixpoint logic) model checking. After a brief introduction to HFL, we explain how it can be applied to program verification,…

Programming Languages · Computer Science 2021-09-13 Naoki Kobayashi

We consider two alternative tests to the Higher Criticism test of Donoho and Jin [Ann. Statist. 32 (2004) 962-994] for high-dimensional means under the sparsity of the nonzero means for sub-Gaussian distributed data with unknown column-wise…

Statistics Theory · Mathematics 2013-12-19 Ping-Shou Zhong , Song Xi Chen , Minya Xu

The object of study is the problem of testing for uniformity of the multinomial distribution. We consider tests based on symmetric statistics, defined as the sum of some function of cell-frequencies. Mainly, attention is focused on the…

Statistics Theory · Mathematics 2022-09-12 Sherzod M. Mirakhmedov

The area under the ROC curve is widely used as a measure of performance of classification rules. However, it has recently been shown that the measure is fundamentally incoherent, in the sense that it treats the relative severities of…

Methodology · Statistics 2013-08-02 David J. Hand , Christoforos Anagnostopoulos

Higher criticism, or second-level significance testing, is a multiple-comparisons concept mentioned in passing by Tukey. It concerns a situation where there are many independent tests of significance and one is interested in rejecting the…

Statistics Theory · Mathematics 2007-06-13 David Donoho , Jiashun Jin

We consider the problem of testing distribution identity. Given a sequence of independent samples from an unknown distribution on a domain of size n, the goal is to check if the unknown distribution approximately equals a known distribution…

Data Structures and Algorithms · Computer Science 2009-10-20 Krzysztof Onak
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