Comparative Study of Two Kernel Smoothing Techniques
نویسندگان
چکیده
The kernel functions (kernels) can be used in many types of nonparametric 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 nonparametric method uses so-called frames overcomplet 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 the smoothing procedures are applied to simulated data. Obtained results will be presented graphically.
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