Geographically weighted regression modeling for multiple outcomes
學年 110
學期 1
出版（發表）日期 2022-01-07
作品名稱 Geographically weighted regression modeling for multiple outcomes
作品名稱（其他語言）
著者 Vivian Yi-Ju Chen; Tse-Chuan Yang; Hong-Lian Jian
單位
出版者
著錄名稱、卷期、頁數 Annals of the Association of American Geographer
摘要 Geographically weighted regression (GWR) has been a popular tool applied in various disciplines to explore spatial nonstationarity for georeferenced data. Such a technique, however, typically restricts the analysis to a single outcome variable and a set of explanatory variables. When analyzing multiple interrelated response variables, GWR fails to provide sufficient information about the data because it only allows separate modeling for each response variable. This study attempts to address this gap by introducing a geographically weighted multivariate multiple regression (GWMMR) technique that not only explores spatial nonstationarity but also accounts for correlations across multivariate responses. We first present the model specification of the proposed method and then draw the associated statistical inferences. Several modeling issues are discussed. We also examine finite sample properties of GWMMR using simulation. For an empirical illustration, the new technique is applied to the stop-and-frisk data published by the New York Police Department. The results demonstrate the usefulness of the GWMMR.
關鍵字 geographically weighted regression;multiple outcomes;multivariate multiple regression;spatial nonstationarity
語言 en
ISSN 2469-4452
期刊性質 國外
收錄於 SCI SSCI Scopus ABS* NotTSSCI
產學合作
通訊作者
審稿制度 是
國別 USA
公開徵稿
出版型式 ,電子版,紙本
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