A difference-based approach in the partially linear model with dependent errors
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Publication:824814
DOI10.1186/s13660-018-1857-xzbMath1498.62079OpenAlexW2892750187WikidataQ58581135 ScholiaQ58581135MaRDI QIDQ824814
Publication date: 15 December 2021
Published in: Journal of Inequalities and Applications (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1186/s13660-018-1857-x
Asymptotic properties of nonparametric inference (62G20) Nonparametric estimation (62G05) Numerical solutions to stochastic differential and integral equations (65C30)
Related Items (3)
Asymptotic normality and mean consistency of LS estimators in the errors-in-variables model with dependent errors ⋮ Difference-based M-estimator of generalized semiparametric model with NSD errors ⋮ Statistical inferences in a partially linear model with autoregressive errors
Cites Work
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- A partially linear framework for massive heterogeneous data
- Asymptotic normality of DHD estimators in a partially linear model
- Difference-based ridge estimator of parameters in partial linear model
- Difference based estimation for partially linear regression models with measurement errors
- Convergence rates of wavelet estimators in semiparametric regression models under NA samples
- Difference based ridge and Liu type estimators in semiparametric regression models
- Wavelet estimation of partially linear models
- Asymptotic behavior of robust estimators of regression and scale parameters with fixed carriers
- An elementary estimator of the partial linear model
- Nonparametric estimation of a quantile density function by wavelet methods
- On the strong convergence for weighted sums of negatively superadditive dependent random variables
- Asymptotic properties of wavelet estimators in partially linear errors-in-variables models with long-memory errors
- Efficient estimation in the partially linear quantile regression model for longitudinal data
- Almost sure convergence theorem and strong stability for weighted sums of NSD random variables
- A difference based approach to the semiparametric partial linear model
- On the strong convergence and some inequalities for negatively superadditive dependent sequences
- Strong and weak consistency of LS estimators in the EV regression model with negatively superadditive-dependent errors
- Complete moment convergence for weighted sums of negatively superadditive dependent random variables
- Complete convergence for weighted sums of NSD random variables and its application in the EV regression model
- Penalized spline estimation in the partially linear model
- M-test in linear models with negatively superadditive dependent errors
- Complete moment convergence for arrays of rowwise NSD random variables
- Complete convergence for arrays of rowwise negatively superadditive-dependent random variables and its applications
- Partially linear models with missing response variables and error-prone covariates
- Complete moment convergence for double-indexed randomly weighted sums and its applications
- Some Concepts of Dependence
- Kaplan–Meier estimator and hazard estimator for censored negatively superadditive dependent data
- Restricted difference-based Liu estimator in partially linear model
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