Asymptotic Normality of Nonparametric Kernel Regression Estimation for Missing at Random Functional Spatial Data

Λεπτομέρειες βιβλιογραφικής εγγραφής
Τίτλος: Asymptotic Normality of Nonparametric Kernel Regression Estimation for Missing at Random Functional Spatial Data
Συγγραφείς: Fatimah Alshahrani, Ibrahim M. Almanjahie, Tawfik Benchikh, Omar Fetitah, Mohammed Kadi Attouch
Πηγή: Journal of Mathematics, Vol 2023 (2023)
Στοιχεία εκδότη: Wiley, 2023.
Έτος έκδοσης: 2023
Θεματικοί όροι: Statistics and Probability, Economics and Econometrics, Regression function, Missing data, Social Sciences, Kernel regression, Regularization and Variable Selection Methods, 01 natural sciences, Estimator, Spatial Econometrics and Spatial Data Analysis, Methods for Handling Missing Data in Statistical Analysis, 0502 economics and business, QA1-939, FOS: Mathematics, Panel Data Models, 0101 mathematics, Kernel density estimation, Nonparametric statistics, Asymptotic distribution, 05 social sciences, Statistics, Nonparametric regression, Applied mathematics, Economics, Econometrics and Finance, Sensitivity Analysis, Combinatorics, Physical Sciences, Kernel (algebra), Mathematics
Περιγραφή: This study investigates the estimation of the regression function using the kernel method in the presence of missing at random responses, assuming spatial dependence, and complete observation of the functional regressor. We construct the asymptotic properties of the established estimator and derive the probability convergence (with rates) as well as the asymptotic normality of the estimator under certain weak conditions. Simulation studies are then presented to examine and show the performance of our proposed estimator. This is followed by examining a real data set to illustrate the suggested estimator’s efficacy and demonstrate its superiority. The results show that the proposed estimator outperforms existing estimators as the number of missing at random data increases.
Τύπος εγγράφου: Article
Other literature type
Περιγραφή αρχείου: text/xhtml
Γλώσσα: English
ISSN: 2314-4785
2314-4629
DOI: 10.1155/2023/8874880
DOI: 10.60692/gcehr-39908
DOI: 10.60692/cv0kn-cqj33
Σύνδεσμος πρόσβασης: https://doaj.org/article/7be291691c29444c8a90f977718658b0
Rights: CC BY
Αριθμός Καταχώρησης: edsair.doi.dedup.....a9406c12d5512390511b82492d3ecda8
Βάση Δεδομένων: OpenAIRE
Περιγραφή
ISSN:23144785
23144629
DOI:10.1155/2023/8874880