Nonparametric probability density estimation using normalized b–splines

DOI10.1080/03610919208813053zbMath0775.62093OpenAlexW2038785998MaRDI QIDQ4038793

Kevin R. Gehringer, Richard A. Redner

Publication date: 26 May 1993

Published in: Communications in Statistics - Simulation and Computation (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/03610919208813053

zbMATH Keywords

consistency

Mathematics Subject Classification ID

Density estimation (62G07)

Related Items (8)

Convergence rates for uniform b-spline density estimators part ii: multiple dimensions ⋮ Function estimation using partitions of unity ⋮ Nonparametric probability density estimation using normalized b–splines ⋮ Spline local basis methods for nonparametric density estimation ⋮ Bayesian expectation maximization algorithm by using B-splines functions: application in image segmentation ⋮ Approximation by \(B\)-spline convolution operators. A probabilistic approach ⋮ Convergence rates for uniform B-spline density estimators on bounded and semi-infinite domains ⋮ NONPARAMETRIC DENSITY ESTIMATION BY B-SPLINE DUALITY

Cites Work

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• Optimal convergence properties of variable knot, kernel, and orthogonal series methods for density estimation
• Interpolating spline methods for density estimation. I: Equi-spaced knots
• Nonparametric maximum likelihood estimation of probability densities by penalty function methods
• Mixture Densities, Maximum Likelihood and the EM Algorithm
• Nonparametric probability density estimation using normalized b–splines
• Estimation of Probability Density by an Orthogonal Series
• A Polynomial Algorithm for Density Estimation
• On Estimation of a Probability Density Function and Mode

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