High-performance solutions of geographically weighted regression in R

As an established spatial analytical tool, Geographically Weighted Regression (GWR) has been applied across a variety of disciplines. However, its usage can be challenging for large datasets, which are increasingly prevalent in today’s digital world. In this study, we propose two high-performance R...

وصف كامل

محفوظ في:
التفاصيل البيبلوغرافية
المؤلفون الرئيسيون: Binbin Lu, Yigong Hu, Daisuke Murakami, Chris Brunsdon, Alexis Comber, Martin Charlton, Paul Harris
التنسيق: Artigo
اللغة:Inglês
منشور في: Taylor & Francis Group 2022-05-01
سلاسل:Geo-spatial Information Science
الموضوعات:
Non-stationarity
big data
parallel computing
Compute Unified Device Architecture (CUDA)
Geographically Weighted models (GWmodel)
الوصول للمادة أونلاين:https://www.tandfonline.com/doi/10.1080/10095020.2022.2064244
الوسوم: إضافة وسم
لا توجد وسوم, كن أول من يضع وسما على هذه التسجيلة!

مواد مشابهة