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The classic chi-squared statistic for testing goodness-of-fit has long been a cornerstone of modern statistical practice. The statistic consists of a sum in which each summand involves division by the probability associated with the…

Computation · Statistics 2015-03-17 William Perkins , Mark Tygert , Rachel Ward

This paper extends our earlier article, "Computing the confidence levels for a root-mean-square test of goodness-of-fit;" unlike in the earlier article, the models in the present paper involve parameter estimation -- both the null and…

Computation · Statistics 2011-12-23 William Perkins , Mark Tygert , Rachel Ward

If a discrete probability distribution in a model being tested for goodness-of-fit is not close to uniform, then forming the Pearson chi-square statistic can involve division by nearly zero. This often leads to serious trouble in practice…

Methodology · Statistics 2011-09-16 William Perkins , Mark Tygert , Rachel Ward

Goodness-of-fit tests based on the Euclidean distance often outperform chi-square and other classical tests (including the standard exact tests) by at least an order of magnitude when the model being tested for goodness-of-fit is a discrete…

Methodology · Statistics 2024-04-09 William Perkins , Mark Tygert , Rachel Ward

Pearson's chi-squared test is widely used to test the goodness of fit between categorical data and a given discrete distribution function. When the number of sets of the categorical data, say $k$, is a fixed integer, Pearson's chi-squared…

Methodology · Statistics 2022-01-03 Shuhua Chang , Deli Li , Yongcheng Qi

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

Hypothesis testing is a useful statistical tool in determining whether a given model should be rejected based on a sample from the population. Sample data may contain sensitive information about individuals, such as medical information.…

Statistics Theory · Mathematics 2016-06-03 Marco Gaboardi , Hyun woo Lim , Ryan Rogers , Salil Vadhan

Chi-squared tests for lack of fit are traditionally employed to find evidence against a hypothesized model, with the model accepted if the Karl Pearson statistic comparing observed and expected numbers of observations falling within cells…

Statistics Theory · Mathematics 2021-12-20 Robert G. Staudte

We consider goodness-of-fit tests for uniformity of a multinomial distribution by means of tests based on a class of symmetric statistics, defined as the sum of some function of cell-frequencies. We are dealing with an asymptotic regime,…

Statistics Theory · Mathematics 2022-11-03 Sherzod M Mirakhmedov

We consider testing equivalence to Hardy-Weinberg Equilibrium in case of multiple alleles. Two different test statistics are proposed for this test problem. The asymptotic distribution of the test statistics is derived. The corresponding…

Methodology · Statistics 2025-07-15 Vladimir Ostrovski

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

It is well known that the approximate distribution of the usual test statistic of a goodness-of-fit test is chi-square, with degrees of freedom equal to the number of categories minus 1 (assuming that no parameters are to be estimated --…

Statistics Theory · Mathematics 2014-10-28 Kris Duszak , Jan Vrbik

This paper introduces chi-square goodness-of-fit tests to check for conditional distribution model specification. The data is cross-classified according to the Rosenblatt transform of the dependent variable and the explanatory variables,…

Econometrics · Economics 2023-09-25 Miguel A. Delgado , Julius Vainora

Recent years have witnessed a controversy over Heisenberg's famous error-disturbance relation. Here we resolve the conflict by way of an analysis of the possible conceptualizations of measurement error and disturbance in quantum mechanics.…

Quantum Physics · Physics 2014-12-24 Paul Busch , Pekka Lahti , Reinhard F Werner

For testing goodness of fit, we consider a class of U-statistics of overlapping spacings of order two, and investigate their asymptotic properties. The standard U-statistic theory is not directly applicable here as the overlapping spacings…

Statistics Theory · Mathematics 2024-05-14 Rahul Singh , Neeraj Misra

Weighted histograms are used for the estimation of probability density functions. Computer simulation is the main domain of application of this type of histogram. A review of chi-square goodness of fit tests for weighted histograms is…

Data Analysis, Statistics and Probability · Physics 2015-05-13 Nikolai Gagunashvili

Under complete linkage disequilibrium (LD), robust tests often have greater power than Pearson's chi-square test and trend tests for the analysis of case-control genetic association studies. Robust statistics have been used in…

Methodology · Statistics 2010-10-26 Gang Zheng , Jungnam Joo , Dmitri Zaykin , Colin Wu , Nancy Geller

This work proposes a new method for computing acceptance regions of exact multinomial tests. From this an algorithm is derived, which finds exact p-values for tests of simple multinomial hypotheses. Using concepts from discrete convex…

Computation · Statistics 2023-05-31 Johannes Resin

The Ratio Test and the Root Test for absolute convergence/divergence of series of numbers $\sum_{n=0}^{\infty}a_n$ are frequently discussed and proved independently in Calculus courses. The Root Test is stronger (verifies convergence for…

History and Overview · Mathematics 2024-10-03 Victoria Rayskin

A consistent goodness-of-fit test for distributional regression is introduced. The test statistic is based on a process that traces the difference between a nonparametric and a semi-parametric estimate of the marginal distribution function…

Methodology · Statistics 2025-10-10 Gitte Kremling , Gerhard Dikta
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