Affiliation:
1. Department of Statistics, Bogor Agricultural University, Bogor, West Java, Indonesia
Abstract
Geographically weighted regression (GWR) is development of multiple regression that has spatial varying, so that the estimator of GWR is different for each location. Parameter estimation in GWR uses weighted least square method which is vulnerable to outlier and can cause biased parameter estimation. The robust GWR (RGWR) with LAD and M-estimator is resistance to outliers. This research estimated parameters on RGWR using LAD and M-estimator method and uses data of Java gross domestic product (GRDP) in 2015 containing several outliers. The result showed that RGWR model was better than GWR with M-estimator, and the predictions were closer to the actual values.
Reference12 articles.
1. A. B. Author, “Title of chapter in the book,” in Title of His Published Book, xth ed. City of Publisher, Country if not
2. Afifah R. 2017. Robust Geographically Weighted Regression with Least Absolute Deviation Method in Case of Poverty in Java Island. 1827(1):020023. doi: 10.1063/14979439.
3. Anselin L. 1988. Spatial Econometrics: Method and Models. Kluwer Academic Publisher. The Netherlands.
4. Azizah RI. 2015. Pendugaan Parameter Model Dinamik Dengan Metode Median Absolute Deviation dan Bisquare M-Estimation [Skripsi]. Bogor : Institut Pertanian Bogor.
5. [BI] Bank Indonesia. 2015. Metadata : Produk Domestik Regional Bruto (PDRB). Jakarta : Bank Indonesia.
Cited by
1 articles.
订阅此论文施引文献
订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献