Results 11 to 20 of about 158,439 (301)
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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On the Power of Some Nonparametric Isotropy Tests
Acta Universitatis Lodziensis. Folia Oeconomica, 2020 In this paper, properties of nonparametric significance tests verifying the random field isotropy hypothesis are discussed. In particular, the subject of the conducted analysis is the probability of rejecting the null hypothesis when it is true.
Krzysztof Szymoniak-Książek
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Sign, Wilcoxon and Mann-Whitney Tests for Functional Data: An Approach Based on Random Projections
Mathematics, 2020 Sign, Wilcoxon and Mann-Whitney tests are nonparametric methods in one or two-sample problems. The nonparametric methods are alternatives used for testing hypothesis when the standard methods based on the Gaussianity assumption are not suitable to be ...
Rafael Meléndez +2 more
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A Nonparametric Test of the Leverage Hypothesis [PDF]
SSRN Electronic Journal, 2012 The so-called leverage hypothesis is that negative shocks to prices/returns aect volatility more than equal positive shocks. Whether this is attributable to changing nancial leverage is still subject to dispute but the terminology is in wide use. There are many tests of the leverage hypothesis using discrete time data.
Oliver Linton +2 more
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NonpModelCheck: An R Package for Nonparametric Lack-of-Fit Testing and Variable Selection
Journal of Statistical Software, 2017 We describe the R package NonpModelCheck for hypothesis testing and variable selection in nonparametric regression. This package implements functions to perform hypothesis testing for the significance of a predictor or a group of predictors in a fully ...
Adriano Zanin Zambom, Michael G. Akritas
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Nonparametric Hypothesis Tests for Statistical Dependency [PDF]
IEEE Transactions on Signal Processing, 2004 Determining the structure of dependencies among a set of variables is a common task in many signal and image processing applications, including multitarget tracking and computer vision. In this paper, we present an information-theoretic, machine learning approach to problems of this type. We cast this problem as a hypothesis test between factorizations
A.T. Ihler, J.W. Fisher, A.S. Willsky
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Application of the empirical Bayes approach to nonparametric testing for high-dimensional data
Lietuvos Matematikos Rinkinys, 2010 In [5] a simple, data-driven and computationally efficient procedure of (nonparametric) testing for high-dimensional data have been introduced. The procedure is based on randomization and resampling, a special sequential data partition procedure, and χ2 ...
Gintautas Jakimauskas +1 more
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Universal Codes as a Basis for Time Series Testing [PDF]
, 2005 We suggest a new approach to hypothesis testing for ergodic and stationary processes. In contrast to standard methods, the suggested approach gives a possibility to make tests, based on any lossless data compression method even if the distribution law of
Astola, Jaakko, Ryabko, Boris
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Bootstrap Statistical Inference for the Variance Based on Fuzzy Data
Austrian Journal of Statistics, 2016 The bootstrap is a simple and straightforward method for calculating approximated biases, standard deviations, confidence intervals, testing statistical hypotheses, and so forth, in almost any nonparametric estimation problem. In this paper we describe a
Mohammad Ghasem Akbari +1 more
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Testing jumps via false discovery rate control. [PDF]
PLoS ONE, 2013 Many recently developed nonparametric jump tests can be viewed as multiple hypothesis testing problems. For such multiple hypothesis tests, it is well known that controlling type I error often makes a large proportion of erroneous rejections, and such ...
Yu-Min Yen
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