"627795" . . "[B475747A037B]" . "Some stabilized bandwidth selectors for nonparametric regression"@en . "RIV/00216224:14310/03:00021253!RIV08-MSM-14310___" . "SK - Slovensk\u00E1 republika" . . . . . "14310" . "RIV/00216224:14310/03:00021253" . "12" . . "1"^^ . . . "1335-3632" . . . "Stabiliza\u010Dn\u00ED metody pro hled\u00E1n\u00ED optim\u00E1ln\u00ED \u0161\u00ED\u0159ky okna pro neparametrickou regresi"@cs . "1"^^ . "Some stabilized bandwidth selectors for nonparametric regression" . . "4"^^ . "Stabiliza\u010Dn\u00ED metody pro hled\u00E1n\u00ED optim\u00E1ln\u00ED \u0161\u00ED\u0159ky okna pro neparametrickou regresi"@cs . . . "Some stabilized bandwidth selectors for nonparametric regression"@en . "Pr\u00E1ce se zab\u00FDv\u00E1 n\u011Bkter\u00FDmi metodami pro v\u00FDb\u011Br optim\u00E1ln\u00ED \u0161\u00ED\u0159ky okna p\u0159i neparametrick\u00E9 regresi."@cs . "65-68" . "The problem of bandwidth selection for nonparametric kernel regression is considered. It is well recognized that the classical bandwidth selectors are subject to large sample variation. Due to the large variation, these selectors might not be very useful in practice. Most of bandwidth selectors are based on the residual sum of squares (RSS), the source of the variation is pointed out. The observation leads to consideration of a procedure which stabilizes the RSS by modifying the periodogram of the observations. We will follow the Nadaraya - Watson estimators especially. In a simulation study, it is confirmed that the stabilized bandwidth selectors perform much better than the classical selectors." . "Kol\u00E1\u010Dek, Jan" . "Kernel regression; bandwidth selector; Nadaraya - Watson estimators; periodogram"@en . . "54" . "Journal of Electrical Engineering" . "Z(MSM 143100001)" . . "The problem of bandwidth selection for nonparametric kernel regression is considered. It is well recognized that the classical bandwidth selectors are subject to large sample variation. Due to the large variation, these selectors might not be very useful in practice. Most of bandwidth selectors are based on the residual sum of squares (RSS), the source of the variation is pointed out. The observation leads to consideration of a procedure which stabilizes the RSS by modifying the periodogram of the observations. We will follow the Nadaraya - Watson estimators especially. In a simulation study, it is confirmed that the stabilized bandwidth selectors perform much better than the classical selectors."@en . "Some stabilized bandwidth selectors for nonparametric regression" . .