A note on the asymptotic properties of the estimators in a semiparametric regression model
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Publication:5082818
DOI10.1080/03610918.2019.1652316OpenAlexW2969509761WikidataQ127355535 ScholiaQ127355535MaRDI QIDQ5082818
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Publication date: 21 June 2022
Published in: Communications in Statistics - Simulation and Computation (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1080/03610918.2019.1652316
simulation studyuniform consistencysemiparametric regression model\(\varphi\)-mixing random variables\(r\)-th mean consistency
Related Items (2)
Complete f-moment convergence for arrays of rowwise m-negatively associated random variables and its statistical applications ⋮ Weak consistency for the estimators in a semiparametric regression model based on negatively associated random errors
Cites Work
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- Complete convergence of weighted sums for arrays of rowwise \(\varphi \)-mixing random variables.
- On complete convergence for weighted sums of \(\varphi \)-mixing random variables
- Berry-Esséen bound of sample quantiles for \(\varphi \)-mixing random variables
- An invariance principle for \(\phi\)-mixing sequences
- Almost sure invariance principles for mixing sequences of random variables
- Weak convergence of multidimensional empirical processes for stationary \(\varphi\)-mixing processes
- On consistency of the weighted least squares estimators in a semiparametric regression model
- Some Baum-Katz type results for \({\varphi}\)-mixing random variables with different distributions
- The von Bahr-Esseen moment inequality for pairwise independent random variables and applications
- The asymptotic properties of the estimators in a semiparametric regression model
- Strong laws for weighted sums of \(\psi \)-mixing random variables and applications in errors-in-variables regression models
- Fixed-design semiparametric regression for linear time series
- An almost sure central limit theorem for self-normalized weighted sums of the φ mixing random variables
- On the Rate of Complete Convergence for Weighted Sums of Arrays of Rowwise ϕ-Mixing Random Variables
- On the Central Limit Theorem for $\varphi$-Mixing Arrays of Random Variables
- The invariance principle for ϕ-mixing sequences
- A Note on the Berry-Esséen Bound of Sample Quantiles for ϕ-mixing Sequence
- On Complete Convergence for Nonstationary ϕ-Mixing Random Variables
- A general result on complete convergence for weighted sums of linear processes and its statistical applications
- A Note on Weak Convergence of Empirical Processes for Sequences of $\phi$- Mixing Random Variables
- On the rates of asymptotic normality for recursive kernel density estimators under ϕ-mixing assumptions
- Precise Rates in the Law of Iterated Logarithm for the Moment Convergence of φ-Mixing Sequences
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