On the Equality of Two Distributions Based on Nonparametric Kernel Density Estimator

  • Published : 2003.05.31

Abstract

Hypothesis testing for the equality of two distributions were considered. Nonparametric kernel density estimates were used for testing equality of distributions. Cross-validatory choice of bandwidth was used in the kernel density estimation. Sampling distribution of considered test statistic were developed by resampling method, called the bootstrap. Small sample Monte Carlo simulation were conducted. Empirical power of considered tests were compared for variety distributions.

Keywords

References

  1. Journal of the American Statistical Association v.51 Hypothesis Testingf Using an L₁Distance Bootstrap. Allen, D. L.
  2. Jber. Math. Verin. v.86 Bootstrap Methods in Statistics Beran, R.
  3. The Annals of Statistics v.19 Central Limit Theorems for $L_{p}$ Distances of Kernel Estimators of Densities Under Random Csorgo, M.;Gomby, E.;Horvath
  4. Ann. of Statist. Bootstrap methods: Another look at the jackknife Efron, B.
  5. An introduction of the Bootstrap Efron, B.;Tibshirani, R.J.
  6. Density Estimation for Statistics and Data Analysis Silverman, B. W.