Optimal prediction for linear regression with infinitely many parameters.

DOI10.1016/S0047-259X(02)00006-4zbMath1038.62058MaRDI QIDQ1867192

Alexander Goldenshluger, Alexandre B. Tsybakov

Publication date: 2 April 2003

Published in: Journal of Multivariate Analysis (Search for Journal in Brave)

zbMATH Keywords

asymptotics of minimax riskLinear regression with infinitely many parametersOptimal predictionPinsker filter

Mathematics Subject Classification ID

Asymptotic properties of parametric estimators (62F12) Inference from stochastic processes and prediction (62M20) Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Linear regression; mixed models (62J05)

Related Items

Sharp adaptive estimation by a blockwise method, Adaptive estimation of linear functionals in functional linear models, Asymptotic minimax risk of predictive density estimation for non-parametric regression, Ridge regression and asymptotic minimax estimation over spheres of growing dimension, Evaluation and selection of models for out-of-sample prediction when the sample size is small relative to the complexity of the data-generating process, Adaptive functional linear regression, Adaptive prediction and estimation in linear regression with infinitely many parameters.

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