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- W1596564667 abstract "The problem of adaptive prediction and estimation in the stochastic linear regression model with infinitely many parameters is considered.We suggest a prediction method that is sharp asymptotically minimax adaptive over ellipsoids in $ell_2$. The method consists in an application of blockwise Stein’s rule with “weakly” geometrically increasing blocks to the penalized least squares fits of the first $N$ coefficients. To prove the results we develop oracle inequalities for a sequence model with correlated data." @default.
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- W1596564667 date "2001-12-01" @default.
- W1596564667 modified "2023-09-26" @default.
- W1596564667 title "Adaptive Prediction and Estimation in Linear Regression with Infinitely Many Parameters" @default.
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- W1596564667 doi "https://doi.org/10.1214/aos/1015345956" @default.
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