Asymptotic properties of the multivariate Nadaraya-Watson regression function estimate: The fixed design case

DOI10.1016/0167-7152(88)90085-5zbMath0662.62038OpenAlexW2089351088MaRDI QIDQ1113582

Alexander A. Georgiev

Publication date: 1988

Published in: Statistics \& Probability Letters (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/0167-7152(88)90085-5

zbMATH Keywords

regression functionconsistentasymptotically normalsmoothed Nadaraya-Watson estimate

Mathematics Subject Classification ID

Nonparametric estimation (62G05)

Related Items (10)

Confidence intervals for nonparametric regression functions with missing data: multiple design case ⋮ On sufficient conditions for the consistency of local linear kernel estimators ⋮ Towards Insensitivity of Nadaraya--Watson Estimators to Design Correlation ⋮ Empirical likelihood for non-parametric regression models with missing responses: multiple design case ⋮ Consistent nonparametric multiple regression for dependent heterogeneous processes: the fixed design case ⋮ Nonparametric multiple function fitting ⋮ Goodness of fit in nonparametric regression modelling ⋮ Strong laws of large numbers for arrays of row-wise extended negatively dependent random variables with applications ⋮ Estimation of the conditional distribution in a conditional Koziol-Green model ⋮ Consistent nonparametric regression: Some generalizations in the fixed design case

Cites Work

• Fitting a multiple regression function
• Nonparametric function recovering from noisy observations
• Consistent nonparametric regression. Discussion
• Nonparametric regression: An up–to–date bibliography
• Kernel Regression Estimation Using Repeated Measurements Data
• Probability Inequalities for Sums of Independent Random Variables
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