Asymptotic normality for estimator of conditional mode under left-truncated and dependent observations
From MaRDI portal
Publication:976952
DOI10.1007/s00184-009-0237-4zbMath1189.62059OpenAlexW2045430107MaRDI QIDQ976952
Han-Ying Liang, Jacobo de Uña-Álvarez
Publication date: 16 June 2010
Published in: Metrika (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1007/s00184-009-0237-4
Density estimation (62G07) Asymptotic properties of nonparametric inference (62G20) Censored data models (62N01)
Related Items (3)
Asymptotic properties for an M-estimator of the regression function with truncation and dependent data ⋮ Asymptotic Properties of the Semi-Parametric Estimators of the Conditional Density for Functional Data in the Single Index Model with Missing Data at Random ⋮ Berry–Esseen type bound of conditional mode estimation under truncation and strong mixing assumptions
Cites Work
- Asymptotic properties of the kernel estimator of the conditional mode for the left truncated model
- Asymptotic properties of the product limit estimate under random truncation
- On weak convergence and optimality of kernel density estimates of the mode
- Mixing: Properties and examples
- Strong convergence of sums of \(\alpha \)-mixing random variables with applications to density estimation
- Estimation of the truncation probability in the random truncation model
- A note on prediction via estimation of the conditional mode function
- A note on density mode estimation
- Almost sure representations of the product-limit estimator for truncated data
- Nonparametric regression estimation for dependent functional data: asymptotic normality
- Some Limit Theorems for Random Functions. I
- Non-parametric estimation of the conditional mode
- A note on the product-limit estimator under right censoring and left truncation
- The asymptotic distributions of kernel estimators of the mode
- On the Asymptotic Normality of the Mode of Multidimensional Distributions
- On the asymptotic normality of the kernel estimators of the density function and its derivatives under censoring
- Local Polynomial Estimation of Regression Functions for Mixing Processes
- A Note on Ergodic Processes Prediction via Estimation of the Conditional Mode Function
- Asymptotic normality of kernel estimators of the conditional mode under strong mixing hypothesis
- On Non-Parametric Estimates of Density Functions and Regression Curves
- Strong uniform consistency of nonparametric estimation of the censored conditional mode function
- On Estimation of a Probability Density Function and Mode
- Estimating a distribution function with truncated data
- Laws of iterated logarithm and related asymptotics for estimators of conditional density and mode
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
This page was built for publication: Asymptotic normality for estimator of conditional mode under left-truncated and dependent observations
