教師資料查詢 | 類別: 期刊論文 | 教師: 陳怡如 Yi-ju Chen (瀏覽個人網頁)

標題:Exploring Heterogeneities with Geographically Weighted Quantile Regression: An Enhancement Based on the Bootstrap Approach
學年
學期
出版(發表)日期2020/10/11
作品名稱Exploring Heterogeneities with Geographically Weighted Quantile Regression: An Enhancement Based on the Bootstrap Approach
作品名稱(其他語言)
著者Vivian Yi‐Ju Chen; Tse‐Chuan Yang; Stephen A. Matthews
單位
出版者
著錄名稱、卷期、頁數Geographical Analysis 52(4), p.642-661
摘要Geographically weighted quantile regression (GWQR) has been proposed as a spatial analytical technique to simultaneously explore two heterogeneities, one of spatial heterogeneity with respect to data relationships over space and one of response heterogeneity across different locations of the outcome distribution. However, one limitation of GWQR framework is that the existing inference procedures are established based on asymptotic approximation, which may suffer computation difficulties or yield incorrect estimates with finite samples. In this article, we suggest a bootstrap approach to address this limitation. Our bootstrap enhancement is first validated by a simulation experiment and then illustrated with an empirical U.S. mortality data. The results show that the bootstrap approach provides a practical alternative for inference in GWQR and enhances the utilization of GWQR.
關鍵字
語言英文
ISSN1538-4632
期刊性質國外
收錄於SSCI;
產學合作
通訊作者
審稿制度
國別美國
公開徵稿
出版型式,電子版,紙本
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