Estimation for spatial semi-functional partial linear regression model with missing response at random
The aim of this article is to study a semi-functional partial linear regression model (SFPLR) for spatial data with responses missing at random (MAR). The estimators are constructed using the kernel method, and some asymptotic properties, such as the probability convergence rates of the nonparametri...
Saved in:
| Main Authors: | Benchikh Tawfik, Almanjahie Ibrahim M., Fetitah Omar, Attouch Mohammed Kadi |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
De Gruyter
2025-03-01
|
| Series: | Demonstratio Mathematica |
| Subjects: | |
| Online Access: | https://doi.org/10.1515/dema-2025-0108 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Nonparametric expectile shortfall regression for functional data
by: Almanjahie Ibrahim M., et al.
Published: (2025-04-01) -
Tree-based conditional copula estimation
by: Bonacina Francesco, et al.
Published: (2025-02-01) -
Conservative inference for counterfactuals
by: Balakrishnan Sivaraman, et al.
Published: (2025-04-01) -
Treatment effect estimation with observational network data using machine learning
by: Emmenegger Corinne, et al.
Published: (2025-04-01) -
Fast estimation of Kendall's Tau and conditional Kendall's Tau matrices under structural assumptions
by: van der Spek Rutger, et al.
Published: (2025-04-01)