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Comment: Quantifying the Fraction of Missing Information for Hypothesis Testing in Statistical and Genetic Studies [PDF]

open access: yesStatistical Science 2008, Vol. 23, No. 3, 318-320, 2011
Comment on "Quantifying the Fraction of Missing Information for Hypothesis Testing in Statistical and Genetic Studies" [arXiv:1102.2774]
arxiv   +2 more sources

Statistical Limits for Testing Correlation of Hypergraphs [PDF]

open access: yesarXiv, 2022
In this paper, we consider the hypothesis testing of correlation between two $m$-uniform hypergraphs on $n$ unlabelled nodes. Under the null hypothesis, the hypergraphs are independent, while under the alternative hypothesis, the hyperdges have the same marginal distributions as in the null hypothesis but are correlated after some unknown node ...
arxiv  

Chi-squared test for hypothesis testing of homogeneity [PDF]

open access: yesarXiv, 2021
We provide necessary and sufficient conditions of uniform consistency of nonparametric sets of alternatives of chi-squared test for testing of hypothesis of homogeneity. The number of cells of chi-squared test increases with sample size growth. Nonparametric sets of alternatives can be defined both in terms of densities and distribution functions.
arxiv  

Rejoinder: Quantifying the Fraction of Missing Information for Hypothesis Testing in Statistical and Genetic Studies [PDF]

open access: yesStatistical Science 2008, Vol. 23, No. 3, 325-331, 2011
Rejoinder to "Quantifying the Fraction of Missing Information for Hypothesis Testing in Statistical and Genetic Studies" [arXiv:1102.2774]
arxiv   +1 more source

Fault Diagnosis using Clustering. What Statistical Test to use for Hypothesis Testing? [PDF]

open access: yesMachine Learning and Applications: An International Journal (MLAIJ), 2019, 2019
Predictive maintenance and condition-based monitoring systems have seen significant prominence in recent years to minimize the impact of machine downtime on production and its costs. Predictive maintenance involves using concepts of data mining, statistics, and machine learning to build models that are capable of performing early fault detection ...
arxiv   +1 more source

Adaptive testing method for ergodic diffusion processes based on high frequency data [PDF]

open access: yesarXiv, 2020
We consider parametric tests for multidimensional ergodic diffusions based on high frequency data. We propose two-step testing method for diffusion parameters and drift parameters. To construct test statistics of the tests, we utilize the adaptive estimator and provide three types of test statistics: likelihood ratio type test, Wald type test and Rao's
arxiv  

Optimal Hypothesis Testing Based on Information Theory [PDF]

open access: yesarXiv, 2023
There has a major problem in the current theory of hypothesis testing in which no unified indicator to evaluate the goodness of various test methods since the cost function or utility function usually relies on the specific application scenario, resulting in no optimal hypothesis testing method.
arxiv  

Robust hypothesis testing and distribution estimation in Hellinger distance [PDF]

open access: yesarXiv, 2020
We propose a simple robust hypothesis test that has the same sample complexity as that of the optimal Neyman-Pearson test up to constants, but robust to distribution perturbations under Hellinger distance. We discuss the applicability of such a robust test for estimating distributions in Hellinger distance.
arxiv  

Private Sequential Hypothesis Testing for Statisticians: Privacy, Error Rates, and Sample Size [PDF]

open access: yesAISTATS 2022, 2022
The sequential hypothesis testing problem is a class of statistical analyses where the sample size is not fixed in advance. Instead, the decision-process takes in new observations sequentially to make real-time decisions for testing an alternative hypothesis against a null hypothesis until some stopping criterion is satisfied.
arxiv  

A Test for the Zero Mean Hypothesis in Cosmology [PDF]

open access: yesPhys. Rev. D 90, 123008 (2014), 2014
One working hypothesis on which analyses of cosmological data are based is the zero ensemble mean hypothesis, which is related to the statistical homogeneity of cosmological perturbations. This hypothesis, however, should be tested by observational data in the current era of precision cosmology.
arxiv   +1 more source

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