Share Email Print
cover

Proceedings Paper

Modeling for spatial multilevel structural data
Author(s): Suqin Min; Xiaoqun He
Format Member Price Non-Member Price
PDF $14.40 $18.00

Paper Abstract

The traditional multilevel model assumed independence between groups. However, the datasets grouped by geographical units often has spatial dependence. The individual is influenced not only by its region but also by the adjacent regions, and level-2 residual distribution assumption of traditional multilevel model is violated. In order to deal with such spatial multilevel data, we introduce spatial statistics and spatial econometric models into multilevel model, and apply spatial parameters and adjacency matrix in traditional level-2 model to reflect the spatial autocorrelation. Spatial lag model express spatial effects. We build spatial multilevel model which consider both multilevel thinking and spatial correlation.

Paper Details

Date Published: 13 March 2013
PDF: 6 pages
Proc. SPIE 8783, Fifth International Conference on Machine Vision (ICMV 2012): Computer Vision, Image Analysis and Processing, 87830R (13 March 2013); doi: 10.1117/12.2013907
Show Author Affiliations
Suqin Min, Communication Univ. of China (China)
Xiaoqun He, Renmin Univ. of China (China)


Published in SPIE Proceedings Vol. 8783:
Fifth International Conference on Machine Vision (ICMV 2012): Computer Vision, Image Analysis and Processing
Yulin Wang; Liansheng Tan; Jianhong Zhou, Editor(s)

© SPIE. Terms of Use
Back to Top