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Hypothesis testing in contingency tables is usually based on asymptotic results, thereby restricting its proper use to large samples. To study these tests in small samples, we consider the likelihood ratio test and define an accurate index,…

Methodology · Statistics 2018-10-04 Natalia L. Oliveira , Carlos A. de B. Pereira , Marcio A. Diniz , Adriano Polpo

For random samples of size n obtained from p-variate normal distributions, we consider the classical likelihood ratio tests (LRT) for their means and covariance matrices in the high-dimensional setting. These test statistics have been…

Statistics Theory · Mathematics 2013-06-04 Tiefeng Jiang , Fan Yang

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

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

New inference methods for the multivariate coefficient of variation and its reciprocal, the standardized mean, are presented. While there are various testing procedures for both parameters in the univariate case, it is less known how to do…

Methodology · Statistics 2020-03-31 Marc Ditzhaus , Łukas Smaga

Particle physics experiments use likelihood ratio tests extensively to compare hypotheses and to construct confidence intervals. Often, the null distribution of the likelihood ratio test statistic is approximated by a $\chi^2$ distribution,…

Data Analysis, Statistics and Probability · Physics 2022-04-06 Sara Algeri , Jelle Aalbers , Knut Dundas Morå , Jan Conrad

In this paper, we show that the likelihood-ratio measure (a) is invariant with respect to dominating sigma-finite measures, (b) satisfies logical consequences which are not satisfied by standard $p$-values, (c) respects frequentist…

Methodology · Statistics 2021-04-07 Alexandre G. Patriota

We consider the problem of hypotheses testing with the basic simple hypothesis: observed sequence of points corresponds to stationary Poisson process with known intensity against a composite one-sided parametric alternative that this is a…

Statistics Theory · Mathematics 2007-06-13 Serguei Dachian , Yury A. Kutoyants

Tests for proportional hazards assumption concerning specified covariates or groups of covariates are proposed. The class of alternatives is wide: log-hazard rates under different values of covariates may cross, approach, go away. The data…

Statistics Theory · Mathematics 2020-01-20 Vilijandas Bagdonavičius , Rūta Levulienė

Testing the equality of two proportions is a common procedure in science, especially in medicine and public health. In these domains it is crucial to be able to quantify evidence for the absence of a treatment effect. Bayesian hypothesis…

The comparison of proportions is considered in the asymptotic generalized linear model with the odds ratio as effect size. When several doses are compared with a control assuming an order restriction, a Williams-type trend test can be used.…

Applications · Statistics 2020-11-30 Ludwig A. Hothorn

For general repeated measures designs the Wald-type statistic (WTS) is an asymptotically valid procedure allowing for unequal covariance matrices and possibly non-normal multivariate observations. The drawback of this procedure is the poor…

Methodology · Statistics 2016-06-24 Sarah Friedrich , Edgar Brunner , Markus Pauly

Power-law distributions occur in wide variety of physical, biological, and social phenomena. In this paper, we propose a statistical hypothesis test based on the log-likelihood ratio to assess whether two samples of discrete data are drawn…

Methodology · Statistics 2015-03-03 Alessandro Bessi

We describe likelihood-based statistical tests for use in high energy physics for the discovery of new phenomena and for construction of confidence intervals on model parameters. We focus on the properties of the test procedures that allow…

Data Analysis, Statistics and Probability · Physics 2013-06-25 Glen Cowan , Kyle Cranmer , Eilam Gross , Ofer Vitells

This work is concern with testing the low-dimensional parameters of interest with divergent dimensional data and variable selection for the rest under the sparse case. A consistent test via the partial penalized likelihood approach, called…

Methodology · Statistics 2014-11-20 Shanshan Wang , Hengjian Cui

In this paper we propose the use of $\phi$-divergences as test statistics to verify simple hypotheses about a one-dimensional parametric diffusion process $\de X_t = b(X_t, \theta)\de t + \sigma(X_t, \theta)\de W_t$, from discrete…

Statistics Theory · Mathematics 2008-08-22 Alessandro De Gregorio , Stefano Iacus

Many statistical hypotheses can be formulated in terms of polynomial equalities and inequalities in the unknown parameters and thus correspond to semi-algebraic subsets of the parameter space. We consider large sample asymptotics for the…

Statistics Theory · Mathematics 2009-04-03 Mathias Drton

This paper presents the asymptotic distributions of a general likelihood-based test statistic, derived using results of Wilks and Wald. The general form of the test statistic incorporates the test statistics and associated asymptotic…

Data Analysis, Statistics and Probability · Physics 2013-02-13 Will Buttinger

We propose novel methodology for testing equality of model parameters between two high-dimensional populations. The technique is very general and applicable to a wide range of models. The method is based on sample splitting: the data is…

Methodology · Statistics 2013-01-17 Nicolas Städler , Sach Mukherjee

Estimation of the $\phi$-divergence between two unknown probability distributions using empirical data is a fundamental problem in information theory and statistical learning. We consider a multi-variate generalization of the data dependent…

Probability · Mathematics 2018-01-04 Fengqiao Luo , Sanjay Mehrotra