Improvements on strong uniform consistency of some known kernel estimates of a density and its derivatives
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Publication:1262646
DOI10.1016/0167-7152(92)90007-RzbMath0686.62023OpenAlexW2091608789MaRDI QIDQ1262646
K. L. Mehra, Rohana J. Karunamuni
Publication date: 1990
Published in: Statistics \& Probability Letters (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1016/0167-7152(92)90007-r
bias reductionBernstein polynomialsfinite differencessmoothness assumptionsStrong uniform consistencykernel type estimatesrate of convergence results
Related Items (9)
On the convergence of Newton's method when estimating higher dimensional parameters ⋮ Note on the minimum mean integrated squared error of kernel estimates of a distribution function and its derivatives ⋮ Weak and strong uniform consistency rates of kernel density estimates for randomly censored data ⋮ Some results about kernel estimators for function derivatives based on stationary and ergodic continuous time processes with applications ⋮ Deconvolving a density from contaminated dependent observations ⋮ Nonparametric estimation of a regression function and its derivatives under an ergodic hypothesis ⋮ Optimal convergence properties of kernel density estimators without differentiability conditions ⋮ Asymptotics for function derivatives estimators based on stationary and ergodic discrete time processes ⋮ A new smoothness quantification in kernel density estimation
Cites Work
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