Parametric versus nonparametrics: two alternative methodologies
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Publication:3627335
DOI10.1080/10485250902842727zbMath1161.62020OpenAlexW4242384519MaRDI QIDQ3627335
Publication date: 19 May 2009
Published in: Journal of Nonparametric Statistics (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1080/10485250902842727
Nonparametric hypothesis testing (62G10) Asymptotic properties of nonparametric inference (62G20) Parametric hypothesis testing (62F03) Asymptotic properties of parametric tests (62F05)
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Cites Work
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- On adaptive estimation
- Adaptive maximum likelihood estimators of a location parameter
- Sharp upper and lower bounds for asymptotic levels of some statistical tests
- Generalizations of the familywise error rate
- On a Theorem of Pitman
- The Efficiency of Some Nonparametric Competitors of the $t$-Test
- Some Extensions of the Wald-Wolfowitz-Noether Theorem
- A review of some adaptive statistical techniques
- Adaptive Robust Procedures: A Partial Review and Some Suggestions for Future Applications and Theory
- Asymptotically Most Powerful Rank-Order Tests
- Testing Statistical Hypotheses
- An Elementary Method for Obtaining Lower Bounds on the Asymptotic Power of Rank Tests
- Estimates of Location Based on Rank Tests
- On a Theorem by Wald and Wolfowitz
- Asymptotic Properties of the Wald-Wolfowitz Test of Randomness
- A Combinatorial Central Limit Theorem
- The Large-Sample Power of Tests Based on Permutations of Observations
- Power Under Normality of Several Nonparametric Tests
- Statistical Tests Based on Permutations of the Observations