Squared error-based shrinkage estimators of discrete probabilities and their application to variable selection

DOI10.1007/S00362-022-01308-WOpenAlexW4226077210MaRDI QIDQ6099114

Jan Mielniczuk, Małgorzata Łazȩcka

Publication date: 19 June 2023

Published in: Statistical Papers (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s00362-022-01308-w

zbMATH Keywords

shrinkage estimatorvariable selectionGini indexconditional mutual informationdiscrete distributionsquared errorcrossvalidationregularisation parameterstochastic measure of accuracy

Mathematics Subject Classification ID

Statistics (62-XX)

Cites Work

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• Bandwidth choice for nonparametric regression
• Central limit theorem for integrated square error of multivariate nonparametric density estimators
• An introduction to copulas.
• Extent to which least-squares cross-validation minimises integrated square error in nonparametric density estimation
• Large sample optimality of least squares cross-validation in density estimation
• An asymptotically optimal window selection rule for kernel density estimates
• Random approximations to some measures of accuracy in nonparametric curve estimation
• Limit theorems for stochastic measures of the accuracy of density estimators
• Correction to: ``Efficient feature selection using shrinkage estimators
• Efficient feature selection using shrinkage estimators
• Can high-order dependencies improve mutual information based feature selection?
• Bayesian Network Structure Learning with Permutation Tests
• Forward-Backward Selection with Early Dropping
• Elements of Information Theory

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