Relative error prediction: Strong uniform consistency for censoring time series model
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Publication:6107547
DOI10.1080/03610926.2021.1979584OpenAlexW3202965975MaRDI QIDQ6107547
Feriel Bouhadjera, Unnamed Author, Unnamed Author
Publication date: 3 July 2023
Published in: Communications in Statistics - Theory and Methods (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1080/03610926.2021.1979584
strong mixingrelative errorcensored dataregression functionkernel estimateuniform almost sure consistency
Nonparametric regression and quantile regression (62G08) Nonparametric robustness (62G35) Nonparametric estimation (62G05) Estimation in survival analysis and censored data (62N02)
Cites Work
- Unnamed Item
- Unnamed Item
- Relative-error prediction in nonparametric functional statistics: theory and practice
- Uniform convergence of estimator for nonparametric regression with dependent data
- Strong consistency of the internal estimator of nonparametric regression with dependent data
- Relative error prediction via kernel regression smoothers
- Relative-error prediction
- Asymptotic properties of Kaplan-Meier estimator for censored dependent data
- Nonparametric relative error regression for spatial random variables
- Generalized autoregressive conditional heteroscedasticity
- Kernel regression uniform rate estimation for censored data under \(\alpha\)-mixing condition
- Asymptotic theory of weakly dependent stochastic processes
- Relative error prediction for twice censored data
- Nonparametric relative regression under random censorship model
- Nonparametric functional data analysis. Theory and practice.
- Central limit theorem for the kernel estimator of the regression function for censored time series
- Nonparametric Estimation from Incomplete Observations
- Non‐parametric Regression with Dependent Censored Data
- Recursive probability density estimation for weakly dependent stationary processes
- Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation
- Prediction, Linear Regression and the Minimum Sum of Relative Errors
- Nonlinear autoregressive processes
- Estimation with correlated censored survival data with missing covariates
- Estimating a distribution function for censored time series data
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