Asymptotic properties of the kernel estimator of the conditional mode for the left truncated model

DOI10.1016/j.crma.2007.03.023zbMath1113.62041OpenAlexW2094416027MaRDI QIDQ886285

Abdelkader Tatachak, Elias Ould Saïd

Publication date: 26 June 2007

Published in: Comptes Rendus. Mathématique. Académie des Sciences, Paris (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.crma.2007.03.023

Mathematics Subject Classification ID

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

Related Items (13)

NONLINEAR WAVELET ESTIMATION OF CONDITIONAL DENSITY UNDER LEFT-TRUNCATED AND α-MIXING ASSUMPTIONS ⋮ Asymptotic properties of the kernel mode estimator under twice censorship model ⋮ Conditional Quantile Estimation for Truncated and Associated Data ⋮ Asymptotic normality of conditional density estimation under truncated, censored and dependent data ⋮ Strong Consistency Rate for the Kernel Mode Estimator Under Strong Mixing Hypothesis and Left Truncation ⋮ Empirical likelihood for conditional quantile with left-truncated and dependent data ⋮ Kernel estimation of conditional density with truncated, censored and dependent data ⋮ Kernel conditional density and mode estimation for psi-weakly dependent observations ⋮ A weighted estimator of conditional hazard rate with left-truncated and dependent data ⋮ ASYMPTOTIC BEHAVIOR OF A KERNEL CONDITIONAL MODE ESTIMATOR FOR LEFT TRUNCATED AND RIGHT CENSORED DATA ⋮ Asymptotic normality for estimator of conditional mode under left-truncated and dependent observations ⋮ Berry–Esseen type bound of conditional mode estimation under truncation and strong mixing assumptions ⋮ Asymptotic normality of conditional density estimation with left-truncated and dependent data

Cites Work

• Estimation of the truncation probability in the random truncation model
• Almost sure representations of the product-limit estimator for truncated data
• Asymptotic properties of a nonparametric regression function estimator with randomly truncated data
• Non-parametric estimation of the conditional mode
• Estimating a distribution function with truncated data

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