Results 1 to 10 of about 97,834 (258)
Axioms, 2023 Over the last few decades, the statisticians and reliability analysts have looked at putting exponentiality to the test using the Laplace transform technique.
Mahmoud. E. Bakr +1 more
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Truncated Sequential Non-Parametric Hypothesis Testing Based on Random Distortion Testing [PDF]
IEEE Transactions on Signal Processing, 2019 In this paper, we propose a new algorithm for sequential non-parametric hypothesis testing based on Random Distortion Testing (RDT). The data-based approach is non-parametric in the sense that the underlying signal distributions under each hypothesis are assumed to be unknown.
Prashant Khanduri +2 more
exaly +4 more sources
Parametric Predictive Bootstrap Method for the Reproducibility of Hypothesis Tests
Journal of Statistical Theory and PracticeAbstract Hypothesis tests are essential tools in applied statistics, but their results can vary when repeated. The reproducibility probability (RP) quantifies the probability of obtaining the same test outcome—either rejecting or not rejecting the null hypothesis—if a hypothesis test is repeated under identical conditions.
Tahani Coolen-Maturi +2 more
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Non-parametric regression for hypothesis testing in hospitality and tourism research [PDF]
International Journal of Hospitality Management, 2019 Abstract The goal of this paper is to promote the use of Non-Parametric Regression (NPR) for hypothesis testing in hospitality and tourism research. In contrast to linear regression models, NPR frees researchers from the need to impose a priori specification on functional forms, thus allowing more flexibility and less vulnerability to ...
A George Assaf, Efthymios G Tsionas
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Keyed Non-Parametric Hypothesis Tests [PDF]
CoRR, 2020 The recent popularity of machine learning calls for a deeper understanding of AI security. Amongst the numerous AI threats published so far, poisoning attacks currently attract considerable attention. In a poisoning attack the opponent partially tampers the dataset used for learning to mislead the classifier during the testing phase.
Yao Cheng +4 more
openaire +3 more sources
Stochastic process computational modeling for learning research
Освітній вимір, 2022 The goal of our research was to compare and systematize several approaches to non-parametric null hypothesis significance testing using computer-based statistical modeling.
Oleksandr H. Kolgatin +2 more
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Conditional Inference in Small Sample Scenarios Using a Resampling Approach
Stats, 2021 This paper discusses a non-parametric resampling technique in the context of multidimensional or multiparameter hypothesis testing of assumptions of the Rasch model.
Clemens Draxler, Andreas Kurz
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An Entropy-Based Approach for Nonparametrically Testing Simple Probability Distribution Hypotheses
Econometrics, 2022 In this paper, we introduce a flexible and widely applicable nonparametric entropy-based testing procedure that can be used to assess the validity of simple hypotheses about a specific parametric population distribution. The testing methodology relies on
Ron Mittelhammer +2 more
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Landmark-free, parametric hypothesis tests regarding two-dimensional contour shapes using coherent point drift registration and statistical parametric mapping [PDF]
PeerJ Computer Science, 2021 This paper proposes a computational framework for automated, landmark-free hypothesis testing of 2D contour shapes (i.e., shape outlines), and implements one realization of that framework.
Todd C. Pataky +3 more
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Review of Islamic Social Finance and Entrepreneurship, 2023 Purpose – This study aims to describe the perception of the importance of philanthropy in today's difficult times according to the classification of generations based on Beresford.
Endro Tri Susdarwono, S. Thoriqul Huda
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