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Theory and Practice of Kernel Smoothing - habilitation thesis
Authors | |
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Year of publication | 2015 |
MU Faculty or unit | |
Citation | |
Description | Our main research interest lies in the theory of kernel smoothing. Kernel methods are well-known and intensively used by the community of nonparametricians because they are a useful tool for local weighting. Kernel estimators combine two main advantages: simple expression and ease of implementation. It is well known that the most important factor in kernel estimation is a choice of smoothing parameters. This choice is particularly important because of its role in controlling both the amount and the direction of smoothing. This problem has been widely discussed in many monographs and papers. The following overview starts with a motivation of the theory of kernel smoothing and then briefly describes the main contributions of the book [1] and the papers [2 – 10]. In order to make the presentation more compact, the thesis consists of the author’s selected papers in the area. In References one can find the list of other related publications of the author [11 – 28]. |