Kernel estimation of conditional density with truncated, censored and dependent data

DOI10.1016/j.jmva.2013.05.009zbMath1293.62087OpenAlexW4206240886MaRDI QIDQ391797

Ai-Ai Liu, Han-Ying Liang

Publication date: 13 January 2014

Published in: Journal of Multivariate Analysis (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.jmva.2013.05.009

zbMATH Keywords

asymptotic normalityuniform convergenceconditional density\(\alpha\)-mixingBerry-Esseen type boundtruncated and censored

Mathematics Subject Classification ID

Density estimation (62G07) Asymptotic properties of nonparametric inference (62G20) Estimation in survival analysis and censored data (62N02)

Related Items (8)

Asymptotic normality of conditional density estimation under truncated, censored and dependent data ⋮ Wavelet estimation in varying coefficient models for censored dependent data ⋮ Quantile regression and variable selection for partially linear model with randomly truncated data ⋮ CLT for integrated square error of density estimators with censoring indicators missing at random ⋮ Unnamed Item ⋮ Weighted quantile regression and testing for varying-coefficient models with randomly truncated data ⋮ Bayesian MISE convergence rates of Polya urn based density estimators: asymptotic comparisons and choice of prior parameters ⋮ Single-index quantile regression with left truncated data

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