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

PSC In The News

RSS Feed icon

Lam looks at population and development in next 15 years in UN commission keynote address

Mitchell et al. find harsh family environments may magnify disadvantage via impact on 'genetic architecture'

Frey says Arizona's political paradoxes explained in part by demography

Highlights

PSC newsletter spring 2014 issue now available

Kusunoki wins faculty seed grant award from Institute for Research on Women and Gender

2014 PAA Annual Meeting, May 1-3, Boston

USN&WR ranks Michigan among best in nation for graduate education in sociology, public health, economics

Next Brown Bag

Monday, April 21
Grant Miller: Managerial Incentives in Public Service Delivery

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