Using the bootstrap in testing symmetry versus asymmetry
DOI10.1080/03610918708812578zbMath0609.62067OpenAlexW1990451834MaRDI QIDQ3749941
Richard C. Barker, Eugene F. Schuster
Publication date: 1987
Published in: Communications in Statistics - Simulation and Computation (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1080/03610918708812578
normal distributionexponentialempirical distributionchi-squareCauchylognormalcenter of symmetrydouble exponentialButler sup norm testSchuster-Narvarte estimatorsymmetric bootstrap proceduretesting the hypothesis of symmetry
Nonparametric hypothesis testing (62G10) Probabilistic methods, stochastic differential equations (65C99)
Related Items (18)
Cites Work
- Identifying the closest symmetric distribution or density function
- Estimation of shift and center of symmetry based on Kolmogorov-Smirnov statistics
- Bootstrap methods: another look at the jackknife
- A new nonparametric estimator of the center of a symmetric distribution
- Tests for symmetry about an unknown value based on the empirical distribution function
- Nonparametric estimates of standard error: The jackknife, the bootstrap and other methods
- A Test for Asymmetry Associated with the Hodges-Lehmann Estimator
- Testing Symmetry
- Estimating the distribution function of a symmetric distribution
- On estimating a symmetric distribution
- A Cramer Von-Mises Type Statistic for Testing Symmetry
- A Test for Symmetry Using the Sample Distribution Function
- On Testing the Symmetry of Distributions
- On Estimation of a Probability Density Function and Mode
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