Estimating the endpoint of a distribution in the presence of additive observation errors

DOI10.1016/j.spl.2004.01.013zbMath1095.62042OpenAlexW1999617067MaRDI QIDQ1770062

Alexander Goldenshluger, Alexandre B. Tsybakov

Publication date: 7 April 2005

Published in: Statistics \& Probability Letters (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.spl.2004.01.013

zbMATH Keywords

DeconvolutionOptimal rates of convergenceExtreme value distributionEstimation of support of a probability density

Mathematics Subject Classification ID

Density estimation (62G07) Asymptotic properties of nonparametric inference (62G20)

Related Items

Asymptotic and finite sample properties of Hill-type estimators in the presence of errors in observations, On general consistency in deconvolution mode estimation, Endpoint estimation for observations with normal measurement errors, On dealing with the unknown population minimum in parametric inference, Estimating the Upper Support Point in Deconvolution, Consistency of the Hill Estimator for Time Series Observed with Measurement Errors, Learning Topic Models: Identifiability and Finite-Sample Analysis, Estimating an endpoint with high-order moments, Methods for estimation of convex sets, Estimation of the Boundary of a Variable Observed With Symmetric Error, Estimating the support of multivariate densities under measurement error, Estimation of convex supports from noisy measurements, Frontier estimation in the presence of measurement error with unknown variance

Cites Work

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• Minimax theory of image reconstruction
• On estimating the endpoint of a distribution
• The tail of the convolution of densities and its application to a model of HIV-latency time
• On the estimation of a support curve of indeterminate sharpness
• Asymptotical minimax recovery of sets with smooth boundaries
• Estimation of non-sharp support boundaries
• Optimal Rates of Convergence for Deconvolving a Density
• Estimating a Changepoint, Boundary, or Frontier in the Presence of Observation Error
• The Order of the Minimum Variance in a Non-Regular Case