Asymptotic normality of the relative error regression function estimator for censored and time series data
DOI10.1515/demo-2021-0107zbMath1480.62199OpenAlexW3195719212MaRDI QIDQ2076957
Feriel Bouhadjera, Elias Ould Saïd
Publication date: 22 February 2022
Published in: Dependence Modeling (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1515/demo-2021-0107
asymptotic normalitykernel smoothingstrong mixingrelative errorcensored dataregression functionprobability consistency
Nonparametric regression and quantile regression (62G08) Density estimation (62G07) Asymptotic distribution theory in statistics (62E20) Asymptotic properties of nonparametric inference (62G20) Applications of statistics to biology and medical sciences; meta analysis (62P10) Estimation in survival analysis and censored data (62N02)
Uses Software
Cites Work
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- Relative error prediction via kernel regression smoothers
- Nonparametric statistics for stochastic processes. Estimation and prediction.
- Relative-error prediction
- The functional central limit theorem for strongly mixing processes
- Asymptotic properties of Kaplan-Meier estimator for censored dependent data
- Nonlinear time series. Nonparametric and parametric methods
- Survival analysis. Techniques for censored and truncated data.
- Kernel regression uniform rate estimation for censored data under \(\alpha\)-mixing condition
- Asymptotic theory of weakly dependent stochastic processes
- Local least product relative error estimation for varying coefficient multiplicative regression model
- Nonparametric relative regression under random censorship model
- Central limit theorem for the kernel estimator of the regression function for censored time series
- Statistical Analysis of Financial Data in S-Plus
- Remarks on Some Nonparametric Estimates of a Density Function
- Nonparametric Estimation from Incomplete Observations
- Non‐parametric Regression with Dependent Censored Data
- On nonparametric estimation of the regression function under random censorship model
- Nonlinear autoregressive processes
- Estimation with correlated censored survival data with missing covariates
- Estimating equations for hazard ratio parameters based on correlated failure time data
- Statistical models based on counting processes
- Estimating a distribution function for censored time series data
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