  In this paper, we show that a suitably chosen covariance function of a
continuous time, second order stationary stochastic process can be viewed as a
symmetric higher order kernel. This leads to the construction of a higher order
kernel by choosing an appropriate covariance function. An optimal choice of the
constructed higher order kernel that partially minimizes the mean integrated
square error of the kernel density estimator is also discussed.
