Optimal adaptive estimation of the relative density

DOI10.1007/s11749-015-0426-6zbMath1327.62197OpenAlexW2154208473MaRDI QIDQ497865

Claire Lacour, Gaëlle Chagny

Publication date: 25 September 2015

Published in: Test (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s11749-015-0426-6

zbMATH Keywords

model selectionnonparametric estimationtwo-sample problemrelative density

Mathematics Subject Classification ID

Density estimation (62G07) Nonparametric estimation (62G05) Order statistics; empirical distribution functions (62G30)

Related Items (3)

Adaptive estimation in the functional nonparametric regression model ⋮ Nonparametric estimation of a quantile density function by wavelet methods ⋮ Non-parametric Poisson regression from independent and weakly dependent observations by model selection

Uses Software

• reldist

Cites Work

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• Adaptive pointwise estimation of conditional density function
• Bandwidth selection in kernel density estimation: oracle inequalities and adaptive minimax optimality
• Adaptive functional linear regression
• Plug-in bandwidth selector for the kernel relative density estimator
• Density estimation in Besov spaces
• Data-dependent bandwidth choice for a grade density kernel estimate
• Risk bounds for model selection via penalization
• Nonparametric curve estimation. Methods, theory, and applications
• Density estimation by kernel and wavelets methods: optimality of Besov spaces
• Improved methods for bandwidth selection when estimating ROC curves.
• Semiparametric density estimation under a two-sample density ratio model
• Concentration around the mean for maxima of empirical processes
• Nonparametric and semiparametric estimation of the receiver operating characteristic curve
• Density-ratio matching under the Bregman divergence: a unified framework of density-ratio estimation
• Kernel estimators of the ROC curve are better than empirical.
• Minimal penalties for Gaussian model selection
• Adaptive estimation of the transition density of a particular hidden Markov chain
• Nonparametric homogeneity tests
• Quantile Comparison Functions in Two-Sample Problems, With Application to Comparisons of Diagnostic Markers
• Asymptotic Minimax Character of the Sample Distribution Function and of the Classical Multinomial Estimator
• Relative density estimation for left truncated and right censored data
• Empirical likelihood confidence regions for comparison distributions and ROC curves
• An Order Selection Criterion for Testing Goodness of Fit
• The P-P Plot as a Method for Comparing Treatment Effects
• Relative Density-Ratio Estimation for Robust Distribution Comparison
• PenalizationversusGoldenshluger − Lepski strategies in warped bases regression
• "Optimal" One-Sample Distribution-Free Tests and Their Two-Sample Extensions
• The First-Median Test: A Two-Sided Version of the Control Median Test
• Heuristic Approach to the Kolmogorov-Smirnov Theorems
• On a Test of Whether one of Two Random Variables is Stochastically Larger than the Other
• On Information and Sufficiency
• Confidence Limits for an Unknown Distribution Function
• Introduction to nonparametric estimation

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