Adaptive efficient estimation for a function in heteroscedastic regression | Vestnik Tomskogo gosudarstvennogo universiteta. Upravlenie, vychislitelnaja tehnika i informatika – Tomsk State University Journal of Control and Computer Science. 2019. № 49. DOI: 10.17223/19988605/49/9

Adaptive efficient estimation for a function in heteroscedastic regression

The asymptotic properties of the adaptive improved model selection procedure for estimating an unknown function in heteroskedastic regression are studied. It has been established that the procedure is asymptotically effective in the sense of root mean square risk, i.e. the asymptotic root-mean-square risk of the procedure coincides with the corresponding Pinsker constant, which provides an accurate lower limit of risk for all possible estimates. The results of numerical simulation are presented.

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Keywords

mean square risk, oracle inequalities, nonparametric heteroscedastic regression, improved estimation, асимптотическая эффективность, оракульные неравенства, среднеквадратический риск, улучшенное оценивание, непараметрическая гетероскедастичная регрессия, asymptotic efficiency

Authors

Name	Organization	E-mail
Pchelintsev Evgeny A.	Tomsk State University	evgen-pch@yandex.ru
Perelevskiy Svyatoslav S.	Tomsk State University	slavaperelevskiy@mail.ru

Всего: 2

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