Home > Publications . Search All . Browse All . Country . Browse PSC Pubs . PSC Report Series

PSC In The News

RSS Feed icon

Smock discusses the "new American family" on NPR

Pfeffer and colleagues re-examine impacts of community college attendance

Frey explains the minority-majority remapping of America

Highlights

Apply for 2-year NICHD Postdoctoral Fellowships that begin September 2015

PSC Fall 2014 Newsletter now available

Martha Bailey and Nicolas Duquette win Cole Prize for article on War on Poverty

Michigan's graduate sociology program tied for 4th with Stanford in USN&WR rankings

Next Brown Bag

Monday, Dec 1
Linda Waite, Health & Well-Being of Adults over 60

A supplemental indicator of high-value or low-value spatial clustering

Publication Abstract

Zhang, T.L., and Ge Lin. 2006. "A supplemental indicator of high-value or low-value spatial clustering." Geographical Analysis, 38(2): 209-225.

Most test statistics for detecting spatial clustering cannot distinguish between low-value spatial clustering and high-value spatial clustering, and none is designed to explicitly detect high-value clustering, low-value clustering, or both. To fill this void in practice, we introduce an adjustment procedure that can supplement common two-sided spatial clustering tests so that a one-sided conclusion can be reached. The procedure is applied to Moran's I and Tango's C-G in both simulated and real-world spatial patterns. The results show that the adjustment procedure can account for the influence of low-value clusters on high-value clustering and vice versa. The procedure has little effect on the original global testing methods when there is no clustering. When there is a clustering tendency, the procedure can unambiguously distinguish the existence of high-value clusters or low-value clusters or both.

DOI:10.1111/j.0016-7363.2006.00683.x (Full Text)

Browse | Search : All Pubs | Next