scientific article; zbMATH DE number 7578264
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Publication:5101759
Publication date: 30 August 2022
Full work available at URL: http://www.scielo.org.co/scielo.php?script=sci_arttext&pid=S0120-17512008000100001&lng=en&nrm=iso&tlng=es
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Non-parametric \(k\)-sample tests: density functions vs distribution functions ⋮ Unnamed Item ⋮ Unnamed Item
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Cites Work
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- \(K\)-sample tests based on the likelihood ratio
- On smoothing and the bootstrap
- On \(L_ p\)-norms of multivariate density estimators
- Two-sample test statistics for measuring discrepancies between two multivariate probability density functions using kernel-based density estimates
- Remarks on Some Nonparametric Estimates of a Density Function
- K-Sample Analogues of the Kolmogorov-Smirnov and Cramer-V. Mises Tests
- Empirical likelihood tests for two-sample problems via nonparametric density estimation
- Some New Estimates for Distribution Functions
- Several $k$-Sample Kolmogorov-Smirnov Tests
- A k-sample test based on range intervals
- Use of Ranks in One-Criterion Variance Analysis
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