A comparison of higher-order bias Kernel density estimators

Kernel-based density estimators such as variable kernel methods, higher-order kernels, and transformation and multiplicative correction methods are all believed to improve bias reduction. This may be attributed to similarities the mean squared errors of these approaches. However, questions are raised regarding the capability of these approaches in improving statistical analysis for small-to-moderate exploratory purposes.
1. INTRODUCTION Kernel density estimation is by now a well-established technique (see, e.g., Silverman 1986, Scott 1992, and Wand and Jones 1995). Recently, a wide variety of 'sophistications' of the [...]