Higher order values of MISE in kernel density estimation

Abstract

Density estimation is the general approach adopted for the construction of an estimate of the underlying density function for independent and identically distributed random variables. There is need to reduce the error propagation in Kernel Density Estimation. Higher Order values of the exact and asymptotic mean integrated squared error of some kernels are considered. An empirical verification that EMISE is less than AMISE for higher order normal mixture densities is explored through computer algorithms. The effect of small and large values of the window width is examined over equally spaced grid of (0, 0.5].

Journal of the Nigerian Association of Mathematical Physics Vol. 9 2005: pp. 351-356