Nonparametric probability density estimation using normalized b–splines
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Publication:4038793
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
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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