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A Robust, Fully Adaptive M-estimator for Pointwise Estimation in Heteroscedastic Regression
Adaptation Huber contrast Lepski’s method M-estimation minimax estimation nonparamet-ric regression pointwise estimation robust estimation.
2012/9/19
We introduce a robust and fully adaptive method for pointwise estimation in heteroscedastic regression. We allow for noise and design distributions that are unknown and fulfill very weak assumptions o...
Sharp non-asymptotic oracle inequalities for nonparametric heteroscedastic regression models
Adaptive estimation Heteroscedastic regression Nonasymptoticestimation Nonparametric estimation Oracle inequality
2010/3/10
An adaptive nonparametric estimation procedure is constructed
for heteroscedastic regression when the noise variance depends on the
unknown regression. A non-asymptotic upper bound for a quadratic
...
On the bootstrapping heteroscedastic regression models
Bootstrap heteroscedastic regression ordinary least squares estimates
2009/9/21
The distributjons of deviations of point estimators for
parameters of iterest are essential in the evvaluation of the eficiency of
point estimators. The bootstrap method suggested by B. Efron is on...