A Comparison of Higher-Order Bias Kernel Density Estimators
高阶偏差核密度估计方法的比较
We consider many kernel-based density estimators, all theoretically improving bias from O(h 2), as the smoothing parameter h → 0, to O(h 4). Examples include higher-order kernels, variable kernel methods, and transformation and multiplicative bias-correction approaches. We stress the similarities between what appear to be disparate approaches. In particular, we show how the mean squared errors of all methods have the same form. Our main practical contribution is a…