An Open Problem on Strongly Consistent Learning of the Best Prediction for Gaussian Processes

DOI10.1007/978-1-4939-0569-0_12zbMath1337.60052OpenAlexW37994849MaRDI QIDQ2787364

László Györfi, Alessio Sancetta

Publication date: 25 February 2016

Published in: Springer Proceedings in Mathematics & Statistics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/978-1-4939-0569-0_12

zbMATH Keywords

Gaussian processesconditional expectationlinear regressionstrong consistencyergodic processGaussian time seriesdata driven predictor

Mathematics Subject Classification ID

Inference from stochastic processes and prediction (62M20) Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Gaussian processes (60G15) Linear regression; mixed models (62J05)

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