Comparative study of two kernel smoothing techniques

The kernel functions (kernels) can be used in many types of non-parametric methods - estimation of the density function of a random variable, estimation of the hazard function or the regression function. These methods belong to the most efficient non-parametric methods. Another non-parametric method uses so-called frames - overcomplete systems of functions of some type. This paper compares the kernel smoothing and the frame smoothing with frames of a special kind - the kernel functions are used for their construction. Both smoothing procedures are applied to simulated data. Obtained results will be presented graphically.