Informace o publikaci

Bandwidth matrix selectors for kernel regression

Autoři

KOLÁČEK Jan HOROVÁ Ivanka

Rok publikování 2017
Druh Článek v odborném periodiku
Časopis / Zdroj Computational Statistics
Fakulta / Pracoviště MU

Přírodovědecká fakulta

Citace
www http://is.muni.cz/auth/repo/1319858/template_cost.pdf
Doi http://dx.doi.org/10.1007/s00180-017-0709-3
Obor Obecná matematika
Klíčová slova multivariate kernel regression; constrained bandwidth matrix; kernel smoothing; mean integrated square error
Přiložené soubory
Popis Choosing a bandwidth matrix belongs to the class of significant problems in multivariate kernel regression. The problem consists of the fact that a theoretical optimal bandwidth matrix depends on the unknown regression function which to be estimated. Thus data-driven methods should be applied. A method proposed here is based on a relation between asymptotic integrated square bias and asymptotic integrated variance. Statistical properties of this method are also treated. The last two sections are devoted to simulations and an application to real data.
Související projekty: