Iterated Bernstein operators for distribution function and density estimation: balancing between the number of iterations and the polynomial degree
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Publication:1623808
DOI10.1016/j.csda.2014.11.003OpenAlexW1986066894MaRDI QIDQ1623808
Publication date: 23 November 2018
Published in: Computational Statistics and Data Analysis (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1016/j.csda.2014.11.003
Bernstein operatordensity estimationshape restrictionGnedenko testregular histogramroots of operators
Computational methods for problems pertaining to statistics (62-08) Density estimation (62G07) Asymptotic properties of nonparametric inference (62G20)
Related Items (4)
On nonparametric estimation of the latent distribution for ordinal data ⋮ Design‐based inference on Bernstein type estimators for continuous populations ⋮ Efficient and robust density estimation using Bernstein type polynomials ⋮ Asymptotic properties of Bernstein estimators on the simplex
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