Geodesic
Remarks on optimum kernels and optimum boundary kernels
Applications of Mathematics, Tome 53 (2008) no. 4, pp. 305-317 Cet article a éte moissonné depuis la source Czech Digital Mathematics Library

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Kernel smoothers belong to the most popular nonparametric functional estimates used for describing data structure. They can be applied to the fix design regression model as well as to the random design regression model. The main idea of this paper is to present a construction of the optimum kernel and optimum boundary kernel by means of the Gegenbauer and Legendre polynomials.
Kernel smoothers belong to the most popular nonparametric functional estimates used for describing data structure. They can be applied to the fix design regression model as well as to the random design regression model. The main idea of this paper is to present a construction of the optimum kernel and optimum boundary kernel by means of the Gegenbauer and Legendre polynomials.
DOI : 10.1007/s10492-008-0028-7
Classification : 62G05, 62G07, 62G08
Keywords: kernel; optimum kernel; optimum boundary kernel 
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     title = {Remarks on optimum kernels and optimum boundary kernels},
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     zbl = {1194.62039},
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Poměnková, Jitka. Remarks on optimum kernels and optimum boundary kernels. Applications of Mathematics, Tome 53 (2008) no. 4, pp. 305-317. doi: 10.1007/s10492-008-0028-7

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