Record number :
Title of article :
Optimal prediction for linear regression with infinitely many parameters
Author/Authors :
A. Goldenshluger، نويسنده , , Alexander and Tsybakov، نويسنده , , Alexandre، نويسنده ,
Issue Information :
دوفصلنامه با شماره پیاپی سال 2003
Pages :
From page :
To page :
Abstract :
The problem of optimal prediction in the stochastic linear regression model with infinitely many parameters is considered. We suggest a prediction method that outperforms asymptotically the ordinary least squares predictor. Moreover, if the random errors are Gaussian, the method is asymptotically minimax over ellipsoids in ℓ2. The method is based on a regularized least squares estimator with weights of the Pinsker filter. We also consider the case of dynamic linear regression, which is important in the context of transfer function modeling.
Keywords :
Linear regression with infinitely many parameters , Optimal prediction , Pinsker filter , Exact asymptotics of minimax risk
Journal title :
Journal of Multivariate Analysis
Serial Year :
Link To Document :