Conditional Quantile Estimation for Truncated and Associated Data
From MaRDI portal
Publication:5076920
DOI10.1080/03610926.2018.1498895OpenAlexW2907840087WikidataQ128655740 ScholiaQ128655740MaRDI QIDQ5076920
Latifa Adjoudj, Abdelkader Tatachak
Publication date: 17 May 2022
Published in: Communications in Statistics - Theory and Methods (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1080/03610926.2018.1498895
asymptotic normalitykernel estimatorquantile functionstrong uniform consistency rateassociated datarandom left truncation
Density estimation (62G07) Asymptotic distribution theory in statistics (62E20) Asymptotic properties of nonparametric inference (62G20)
Related Items (1)
Cites Work
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- A note on the Lynden-Bell estimator under association
- Probability and moment inequalities for sums of weakly dependent random variables, with applications
- Asymptotic properties of the kernel estimator of the conditional mode for the left truncated model
- Asymptotic properties of a conditional quantile estimator with randomly truncated data
- The central limit theorem under random truncation
- Kernel estimates under association: Strong uniform consistency
- Kaplan-Meier estimator under association
- A Glivenko-Cantelli lemma and weak convergence for empirical processes of associated sequences
- On average derivative quantile regression
- A new weak dependence condition and applications to moment inequalities
- Weak and strong quantile representations for randomly truncated data with applications,
- Estimation of the truncation probability in the random truncation model
- Survival analysis. Techniques for censored and truncated data.
- A strong uniform convergence rate of a kernel conditional quantile estimator under random left-truncation and dependent data
- Conditional quantile estimation with auxiliary information for left-truncated and dependent data
- Almost sure representations of the product-limit estimator for truncated data
- Asymptotic properties of a nonparametric regression function estimator with randomly truncated data
- Asymptotic Properties of Conditional Quantile Estimator Under Left-Truncated and α-Mixing Conditions
- Asymptotic Normality of a Kernel Conditional Quantile Estimator Under Strong Mixing Hypothesis and Left-Truncation
- Asymptotics for Associated Random Variables
- Local Linear Quantile Regression
- Inverse Gaussian Model and Its Applications in Reliability and Survival Analysis
- Strong Consistency Rate for the Kernel Mode Estimator Under Strong Mixing Hypothesis and Left Truncation
- Association of Random Variables, with Applications
- Estimating a distribution function with truncated data
- Survival function and density estimation for truncated dependent data
This page was built for publication: Conditional Quantile Estimation for Truncated and Associated Data