Rates of consistency for nonparametric estimation of the mode in absence of smoothness assumptions
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Publication:1881236
DOI10.1016/j.spl.2004.04.005zbMath1086.62046OpenAlexW1991962122MaRDI QIDQ1881236
Publication date: 4 October 2004
Published in: Statistics \& Probability Letters (Search for Journal in Brave)
Full work available at URL: https://www.db-thueringen.de/servlets/MCRFileNodeServlet/dbt_derivate_00008620/IfM_Preprint_M_03_14.pdf
Nonparametric regression and quantile regression (62G08) Density estimation (62G07) Asymptotic properties of nonparametric inference (62G20) Nonparametric estimation (62G05)
Related Items (17)
A note on the convergence rate of the kernel density estimator of the mode ⋮ A Statistical Learning Approach to Modal Regression ⋮ Strong Consistency Rate for the Kernel Mode Estimator Under Strong Mixing Hypothesis and Left Truncation ⋮ Some results about kernel estimators for function derivatives based on stationary and ergodic continuous time processes with applications ⋮ On general consistency in deconvolution mode estimation ⋮ Asymptotic normality of the regression mode in the nonparametric random design model for censored data ⋮ On the strong uniform consistency of the mode estimator for censored time series ⋮ Minimax estimation of the mode of functional data ⋮ Some asymptotic properties of kernel regression estimators of the mode for stationary and ergodic continuous time processes ⋮ Uniform rate of strong consistency for a smooth kernel estimator of the conditional mode for censored time series ⋮ A kernel mode estimate under random left truncation and time series model: asymptotic normality ⋮ Limit distribution theory for maximum likelihood estimation of a log-concave density ⋮ Bivariate density estimation using BV regularisation ⋮ On optimal estimation of a non-smooth mode in a nonparametric regression model with \(\alpha \)-mixing errors ⋮ Inference for the mode of a log-concave density ⋮ Asymptotics for function derivatives estimators based on stationary and ergodic discrete time processes ⋮ Kernel estimators of mode under \(\psi\)-weak dependence
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