Results 61 to 70 of about 331,520 (189)
Rank tests are the most important methods of nonparametric statistics. In the introductory part, there are discussions of parametric and nonparametric metods and as a result of those discussions it is established that the rank tests are one of the most ...
Timotijević Marjana
doaj
The paper presents a comparison of the methods for assessing the baseline oil production level based on the use of nonparametric statistics, integral and differential models, and neural network algorithms.
Ivanenko Boris, Petelin Alexander
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Nonparametric Predictive Inference for Reproducibility of Two Basic Tests Based on Order Statistics
Reproducibility of statistical hypothesis tests is an issue of major importance in applied statistics: if the test were repeated, would the same overall conclusion be reached, that is rejection or non-rejection of the null hypothesis?
Frank P.A. Coolen , Hana N. Alqifari
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Nonparametric estimation when data on derivatives are available
We consider settings where data are available on a nonparametric function and various partial derivatives. Such circumstances arise in practice, for example in the joint estimation of cost and input functions in economics.
Hall, Peter, Yatchew, Adonis
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The generalized shrinkage estimator for the analysis of functional connectivity of brain signals
We develop a new statistical method for estimating functional connectivity between neurophysiological signals represented by a multivariate time series. We use partial coherence as the measure of functional connectivity.
Fiecas, Mark, Ombao, Hernando
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Nonparametric Simultaneous Test Procedures
In this research we propose several nonparametric simultaneous test procedures for location and scale parameters. We construct test statistics based on linear rank statistics choosing a suitable combining function.
HYO-IL PARK
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Directions and projective shapes
This paper deals with projective shape analysis, which is a study of finite configurations of points modulo projective transformations. The topic has various applications in machine vision.
Mardia, Kanti V., Patrangenaru, Vic
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On Wasserstein Two-Sample Testing and Related Families of Nonparametric Tests
Nonparametric two-sample or homogeneity testing is a decision theoretic problem that involves identifying differences between two random variables without making parametric assumptions about their underlying distributions. The literature is old and rich,
Aaditya Ramdas +2 more
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Uncertainty Quantification in Load Forecasting for Smart Grids Using Non-Parametric Statistics
In flexibility markets, aggregators serve as crucial intermediaries by consolidating and selling consumer flexibility to grid operators or distribution system operators (DSOs).
Khansa Dab +6 more
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This paper is about two related decision theoretic problems, nonparametric two-sample testing and independence testing. There is a belief that two recently proposed solutions, based on kernels and distances between pairs of points, behave well in high ...
Póczos, Barnabás +4 more
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