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In this paper, we revisit the classical goodness-of-fit problems for univariate distributions; we propose a new testing procedure based on a characterisation of the uniform distribution. Asymptotic theory for the simple hypothesis case is…

Methodology · Statistics 2021-08-17 Bruno Ebner , Shawn Liebenberg , Jaco Visagie

The paper considers a paired data framework and discuss the question of marginal homogeneity of bivariate high dimensional or functional data. The related testing problem can be endowed into a more general setting for paired random…

Methodology · Statistics 2021-05-04 Marc Ditzhaus , Daniel Gaigall

Multivariate goodness-of-fit and two-sample tests are important components of many nuclear and particle physics analyses. While a variety of powerful methods are available if the dimensionality of the feature space is small, such tests…

Data Analysis, Statistics and Probability · Physics 2016-12-22 Constantin Weisser , Mike Williams

Researchers frequently test and improve model fit by holding a sample constant and varying the model. We propose methods to test and improve sample fit by holding a model constant and varying the sample. Much as the bootstrap is a…

Econometrics · Economics 2022-09-15 Gabriel Okasa , Kenneth A. Younge

We present new families of goodness-of-fit tests of uniformity on a full-dimensional set $W\subset\R^d$ based on statistics related to edge lengths of random geometric graphs. Asymptotic normality of these statistics is proven under the…

Statistics Theory · Mathematics 2020-07-20 Bruno Ebner , Franz Nestmann , Matthias Schulte

We propose a new and rather stringent criterion for testing the goodness of fit between a theory and experiment. It is motivated by the paradox that the criterion on \chi^2 for testing a theory is much weaker than the criterion for finding…

High Energy Physics - Phenomenology · Physics 2007-05-23 J. C. Collins , J. Pumplin

Using fixed point characterization, we develop a new goodness of fit test for uniform distribution. We also discuss how the right censored observations can be incorporated in the proposed test procedure. We study the asymptotic properties…

Methodology · Statistics 2021-06-14 Sudheesh K. Kattumannil , Sreedevi E. P

We consider the goodness of fit testing problem for ergodic diffusion processes. The basic hypothesis is supposed to be simple. The diffusion coefficient is known and the alternatives are described by the different trend coefficients. We…

Statistics Theory · Mathematics 2009-03-27 Yury A. Kutoyants

In population genetics and other application fields, models with intractable likelihood are common. Approximate Bayesian Computation (ABC) or more generally Simulation-Based Inference (SBI) methods work by simulating instrumental data sets…

Methodology · Statistics 2025-01-29 Guillaume Le Mailloux , Paul Bastide , Jean-Michel Marin , Arnaud Estoup

This article proposes a class of goodness-of-fit tests for the autocorrelation function of a time series process, including those exhibiting long-range dependence. Test statistics for composite hypotheses are functionals of a (approximated)…

Statistics Theory · Mathematics 2007-06-13 Miguel A. Delgado , Javier Hidalgo , Carlos Velasco

This paper develops goodness of fit statistics that can be used to formally assess Markov random field models for spatial data, when the model distributions are discrete or continuous and potentially parametric. Test statistics are formed…

Statistics Theory · Mathematics 2012-05-29 Mark S. Kaiser , Soumendra N. Lahiri , Daniel J. Nordman

This paper proposes several tests of restricted specification in nonparametric instrumental regression. Based on series estimators, test statistics are established that allow for tests of the general model against a parametric or…

Econometrics · Economics 2019-09-24 Christoph Breunig

Fitting mixture distributions is needed in applications where data belongs to inhomogeneous populations comprising homogeneous sub-populations. The mixing proportions of the sub populations are in general unknown and need to be estimated as…

Methodology · Statistics 2019-12-10 Richard A. Lockhart , Chandanie W. Navaratna

Tests of goodness of fit are used in nearly every domain where statistics is applied. One powerful and flexible approach is to sample artificial data sets that are exchangeable with the real data under the null hypothesis (but not under the…

Methodology · Statistics 2026-04-07 Ritwik Bhaduri , Aabesh Bhattacharyya , Rina Foygel Barber , Lucas Janson

Assessing fit in common factor models solely through the lens of mean and covariance structures, as is commonly done with conventional goodness-of-fit (GOF) assessments, may overlook critical aspects of misfit, potentially leading to…

Methodology · Statistics 2026-03-04 Youjin Sung , Youngjin Han , Yang Liu

Bivariate count models having one marginal and the other conditionals being of the Poissons form are called pseudo-Poisson distributions. Such models have simple exible dependence structures, possess fast computation algorithms and generate…

Applications · Statistics 2023-06-08 Banoth Veeranna , B. G. Manjunath , B. Shobha

We propose a new omnibus goodness-of-fit test based on trigonometric moments of probability-integral-transformed data. The test builds on the framework of the LK test introduced by Langholz and Kronmal [J. Amer. Statist. Assoc. 86 (1991),…

Methodology · Statistics 2026-03-31 Alain Desgagné , Frédéric Ouimet

We propose a novel test statistic for testing exogeneity in the functional linear regression model. In contrast to Hausman-type tests in finite dimensional linear regression setups, a direct extension to the functional linear regression…

Statistics Theory · Mathematics 2022-08-16 Manuela Dorn , Melanie Birke , Carsten Jentsch

Goodness--of--fit tests for the distribution of the composed error term in a Stochastic Frontier Model (SFM) are suggested. The focus is on the case of a normal/gamma SFM and the heavy--tailed stable/gamma SFM. In the first case the moment…

Statistics Theory · Mathematics 2024-08-21 Christos K. Papadimitriou , Simos G. Meintanis , Bernardo B. Andrade , Mike G. Tsionas

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