Nonparametric Spatial Prediction

Citations

Cited by:

1. Younso, Ahmad, 2017. "On the consistency of a new kernel rule for spatially dependent data," Statistics & Probability Letters, Elsevier, vol. 131(C), pages 64-71.
2. Hongxia Wang & Jinde Wang, 2009. "Estimation of the trend function for spatio-temporal models," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 21(5), pages 567-588.
3. Rodrigo García Arancibia & Pamela Llop & Mariel Lovatto, 2023. "Nonparametric prediction for univariate spatial data: Methods and applications," Papers in Regional Science, Wiley Blackwell, vol. 102(3), pages 635-672, June.
4. Ahmad Younso, 2023. "On the consistency of mode estimate for spatially dependent data," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 86(3), pages 343-372, April.
5. Bouabsa Wahiba, 2022. "Unform in Bandwith of the Conditional Distribution Function with Functional Explanatory Variable: The Case of Spatial Data with the K Nearest Neighbour Method," Econometrics. Advances in Applied Data Analysis, Sciendo, vol. 26(2), pages 30-46, June.
6. Mohammed Attouch & Ali Laksaci & Nafissa Messabihi, 2017. "Nonparametric relative error regression for spatial random variables," Statistical Papers, Springer, vol. 58(4), pages 987-1008, December.
7. Rongrong Xu & Jinde Wang, 2008. "-estimation for spatial nonparametric regression," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 20(6), pages 523-537.
8. Benhenni, Karim & Su, Yingcai, 2016. "Optimal sampling designs for nonparametric estimation of spatial averages of random fields," Journal of Multivariate Analysis, Elsevier, vol. 146(C), pages 341-351.
9. El Machkouri, Mohamed & Es-Sebaiy, Khalifa & Ouassou, Idir, 2017. "On local linear regression for strongly mixing random fields," Journal of Multivariate Analysis, Elsevier, vol. 156(C), pages 103-115.
10. Hongxia Wang & Xiao Jin & Jianian Wang & Hongxia Hao, 2023. "Nonparametric Estimation for High-Dimensional Space Models Based on a Deep Neural Network," Mathematics, MDPI, vol. 11(18), pages 1-37, September.
11. Amiri, Aboubacar & Dabo-Niang, Sophie, 2018. "Density estimation over spatio-temporal data streams," Econometrics and Statistics, Elsevier, vol. 5(C), pages 148-170.
12. Sophie Dabo-Niang & Anne-Françoise Yao, 2013. "Kernel spatial density estimation in infinite dimension space," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 76(1), pages 19-52, January.
13. Sophie Dabo-Niang & Sidi Ould-Abdi & Ahmedoune Ould-Abdi & Aliou Diop, 2014. "Consistency of a nonparametric conditional mode estimator for random fields," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 23(1), pages 1-39, March.
14. Nadia Bensaïd & Sophie Dabo-Niang, 2010. "Frequency polygons for continuous random fields," Statistical Inference for Stochastic Processes, Springer, vol. 13(1), pages 55-80, April.
15. Chouaf Abdelhak & Laksaci Ali, 2012. "On the functional local linear estimate for spatial regression," Statistics & Risk Modeling, De Gruyter, vol. 29(3), pages 189-214, August.
16. Salim Bouzebda & Inass Soukarieh, 2022. "Non-Parametric Conditional U -Processes for Locally Stationary Functional Random Fields under Stochastic Sampling Design," Mathematics, MDPI, vol. 11(1), pages 1-69, December.
17. Michel Carbon, 2014. "Histograms for stationary linear random fields," Statistical Inference for Stochastic Processes, Springer, vol. 17(3), pages 245-266, October.
18. Hongxia Wang & Jinde Wang & Bo Huang, 2012. "Prediction for spatio-temporal models with autoregression in errors," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 24(1), pages 217-244.
19. Sophie Dabo-Niang & Zoulikha Kaid & Ali Laksaci, 2015. "Asymptotic properties of the kernel estimate of spatial conditional mode when the regressor is functional," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 99(2), pages 131-160, April.
20. Li, Linyuan, 2015. "Nonparametric adaptive density estimation on random fields using wavelet method," Statistics & Probability Letters, Elsevier, vol. 96(C), pages 346-355.
21. Salim Bouzebda, 2024. "Limit Theorems in the Nonparametric Conditional Single-Index U -Processes for Locally Stationary Functional Random Fields under Stochastic Sampling Design," Mathematics, MDPI, vol. 12(13), pages 1-81, June.
22. Dabo-Niang, Sophie & Kaid, Zoulikha & Laksaci, Ali, 2012. "On spatial conditional mode estimation for a functional regressor," Statistics & Probability Letters, Elsevier, vol. 82(7), pages 1413-1421.
23. Mustapha Rachdi & Ali Laksaci & Noriah M. Al-Kandari, 2022. "Expectile regression for spatial functional data analysis (sFDA)," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 85(5), pages 627-655, July.
24. Mohamed El Machkouri, 2011. "Asymptotic normality of the Parzen–Rosenblatt density estimator for strongly mixing random fields," Statistical Inference for Stochastic Processes, Springer, vol. 14(1), pages 73-84, February.
25. Zudi Lu & Dag Johan Steinskog & Dag Tjøstheim & Qiwei Yao, 2009. "Adaptively varying‐coefficient spatiotemporal models," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 71(4), pages 859-880, September.
26. Sophie Dabo-Niang & Camille Ternynck & Anne-Françoise Yao, 2016. "Nonparametric prediction of spatial multivariate data," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 28(2), pages 428-458, June.
27. Bouzebda, Salim & Slaoui, Yousri, 2019. "Large and moderate deviation principles for recursive kernel estimators of a regression function for spatial data defined by stochastic approximation method," Statistics & Probability Letters, Elsevier, vol. 151(C), pages 17-28.