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Given a random sample of size $n$ from a $p$ dimensional random vector, where both $n$ and $p$ are large, we are interested in testing whether the $p$ components of the random vector are mutually independent. This is the so-called complete…

Statistics Theory · Mathematics 2022-01-24 Yongcheng Qi , Yingchao Zhou

The question of testing for equality in distribution between two linear models, each consisting of sums of distinct discrete independent random variables with unequal numbers of observations, has emerged from the biological research. In…

Statistics Theory · Mathematics 2020-09-01 Giulio Prevedello , Ken R. Duffy

Inference based on the penalized density ratio model is proposed and studied. The model under consideration is specified by assuming that the log--likelihood function of two unknown densities is of some parametric form. The model has been…

Statistics Theory · Mathematics 2008-07-17 Konstantinos Fokianos

Composite likelihood inference has gained much popularity thanks to its computational manageability and its theoretical properties. Unfortunately, performing composite likelihood ratio tests is inconvenient because of their awkward…

Computation · Statistics 2014-08-01 Manuela Cattelan , Nicola Sartori

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

The parametric Welch $t$-test and the non-parametric Wilcoxon-Mann-Whitney test are the most commonly used two independent sample means tests. More recent testing approaches include the non-parametric, empirical likelihood and exponential…

Methodology · Statistics 2019-10-08 Michail Tsagris , Abdulaziz Alenazi , Kleio-Maria Verrou , Nikolaos Pandis

In this paper, in order to test whether changes have occurred in a nonlinear parametric regression, we propose a nonparametric method based on the empirical likelihood. Firstly, we test the null hypothesis of no-change against the…

Statistics Theory · Mathematics 2014-05-22 Gabriela Ciuperca , Zahraa Salloum

We introduce fully nonparametric two-sample tests for testing the null hypothesis that the samples come from the same distribution if the values are only indirectly given via current status censoring. The tests are based on the likelihood…

Statistics Theory · Mathematics 2013-07-12 Piet Groeneboom

Testing the equality in distributions of multiple samples is a common task in many fields. However, this problem for high-dimensional or non-Euclidean data has not been well explored. In this paper, we propose new nonparametric tests based…

Methodology · Statistics 2022-05-30 Hoseung Song , Hao Chen

This paper develops a general methodology to conduct statistical inference for observations indexed by multiple sets of entities. We propose a novel multiway empirical likelihood statistic that converges to a chi-square distribution under…

Methodology · Statistics 2024-08-12 Harold D Chiang , Yukitoshi Matsushita , Taisuke Otsu

So-called linear rank statistics provide a means for distribution-free (even in finite samples), yet highly flexible, two-sample testing in the setting of univariate random variables. Their flexibility derives from a choice of weights that…

Methodology · Statistics 2023-10-03 Dan D. Erdmann-Pham

In a recent paper in this journal [J. Stat. Mech. (2009) P02037] we proposed a new, physically motivated, distribution function for modeling individual incomes having its roots in the framework of the k-generalized statistical mechanics.…

General Finance · Quantitative Finance 2012-12-07 F. Clementi , M. Gallegati , G. Kaniadakis

Given two networks of differing sizes, it is of interest to test whether the two networks belong to the same distribution. We formalize the notion of "equality of distribution" under the framework of the generalized random dot product…

Statistics Theory · Mathematics 2026-03-10 Joshua Agterberg , Minh Tang , Carey Priebe

Survival extropy, which quantifies the uncertainty associated with the remaining lifetime distribution, provides an information-theoretic perspective on survival behavior. We consider a divergence measure based on survival extropy and…

Statistics Theory · Mathematics 2025-12-03 Naresh Garg , Isha Dewan , Sudheesh Kumar Kattumannil

Given that the existing parametric functional forms for the Lorenz curve do not fit all possible size distributions, a universal parametric functional form is introduced. By using the empirical data from different scientific disciplines and…

Data Analysis, Statistics and Probability · Physics 2023-04-28 Thitithep Sitthiyot , Kanyarat Holasut

Inequality indices are quantitative scores that gauge the divergence of wealth distributions in human societies from the "ground state" of pure communism. While inequality indices were devised for socioeconomic applications, they are…

Statistical Mechanics · Physics 2017-03-31 I. Eliazar

Generalized likelihood ratio statistics have been proposed in Fan, Zhang and Zhang [Ann. Statist. 29 (2001) 153-193] as a generally applicable method for testing nonparametric hypotheses about nonparametric functions. The likelihood ratio…

Statistics Theory · Mathematics 2007-06-13 Jianqing Fan , Jian Zhang

The purpose of this paper is to develop and illustrate certain classes of graphical plots that can be used for model verification in quite general survival data and life history data models. By suitably comparing nonparametric and…

Methodology · Statistics 2026-03-25 Nils Lid Hjort , Thomas Lumley

Social inequality manifested across different strata of human existence can be quantified in several ways. Here we compute non-entropic measures of inequality such as Lorenz curve, Gini index and the recently introduced $k$ index…

Physics and Society · Physics 2015-07-17 Jun-ichi Inoue , Asim Ghosh , Arnab Chatterjee , Bikas K. Chakrabarti

Shape constraints yield flexible middle grounds between fully nonparametric and fully parametric approaches to modeling distributions of data. The specific assumption of log-concavity is motivated by applications across economics, survival…

Methodology · Statistics 2024-04-16 Robin Dunn , Aditya Gangrade , Larry Wasserman , Aaditya Ramdas