Comparison between Kriging and GWR for the Spatial Data

被引：0

作者：

Kim, Sun-Woo ^{[1
]}

Jeong, Ae-Ran ^{[1
]}

Lee, Sung-Duck ^{[2
]}

机构：

[1] Chungbuk Natl Univ, Dept Informat & Stat, 12 Gaesin Dong, Cheongju 361763, Chungbuk, South Korea

[2] Chungbuk Natl Univ, Basic Sci Res Inst, Dept Informat & Stat, Cheongju 361763, Chungbuk, South Korea

来源：

KOREAN JOURNAL OF APPLIED STATISTICS | 2005年 / 18卷 / 02期

关键词：

Spatial statistics; Kriging; Semiveriogram; Geographically weighted regression model; PRESS;

D O I：

暂无

中图分类号：

O21 [概率论与数理统计]; C8 [统计学];

学科分类号：

020208 ; 070103 ; 0714 ;

摘要：

Kriging methods as traditional spatial data analysis methods and geographical weighted regression models as statistical analysis methods are compared. In this paper, we apply data from the Ministry of Environment to spatial analysis for practical study. We compare these methods to performance with monthly carbon monoxide observations taken at 116 measuring area of air pollution in 1999.

引用

页码：271 / 280

页数：10

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