Minimum distance histograms with universal performance guarantees

DOI10.1007/s42081-019-00054-yzbMath1436.62123OpenAlexW2959881109WikidataQ127483144 ScholiaQ127483144MaRDI QIDQ2303497

Gloria Teng, Raazesh Sainudiin

Publication date: 4 March 2020

Published in: Japanese Journal of Statistics and Data Science (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s42081-019-00054-y

zbMATH Keywords

model selectiondensity estimationregular pavingrooted planar binary treetree matrix arithmeticYatracos class

Mathematics Subject Classification ID

Density estimation (62G07) Estimation in multivariate analysis (62H12) Nonparametric estimation (62G05)

Related Items (1)

Special feature: Information theory and statistics

Uses Software

• GitHub
• Apache Spark
• MRS 2.0

Cites Work

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• Bin width selection in multivariate histograms by the combinatorial method
• Rates of convergence of minimum distance estimators and Kolmogorov's entropy
• Consistency of data-driven histogram methods for density estimation and classification
• Smoothing of Multivariate Data
• A note on L₁consistent estimation
• Guaranteed Set Computation with Subpavings
• Posterior Expectation of Regularly Paved Random Histograms
• Multivariate Density Estimation by Bayesian Sequential Partitioning
• On the Uniform Convergence of Relative Frequencies of Events to Their Probabilities
• Non-Parametric Estimation II. Statistically Equivalent Blocks and Tolerance Regions--The Continuous Case
• Combinatorial methods in density estimation

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