Small Area Estimation of Proportions with Constraint for National Resources Inventory Survey

Xin Wang, Emily Berg, Zhengyuan Zhu (), Dongchu Sun and Gabriel Demuth
Additional contact information
Xin Wang: Miami University
Emily Berg: Iowa State University
Zhengyuan Zhu: Iowa State University
Dongchu Sun: University of Missouri-Columbia
Gabriel Demuth: Iowa State University

Journal of Agricultural, Biological and Environmental Statistics, 2018, vol. 23, issue 4, No 5, 509-528

Abstract: Abstract Motivated by the need to produce small area estimates for the National Resources Inventory survey, we develop a spatial hierarchical model based on the generalized Dirichlet distribution to construct small area estimators of compositional proportions in several mutually exclusive and exhaustive landcover categories. At the observation level, the standard design-based estimators of the proportions are assumed to follow the generalized Dirichlet distribution. After proper transformation of the design-based estimators, beta regression is applicable. We consider a logit mixed model for the expectation of the beta distribution, which incorporates covariates through fixed effects and spatial effect through a conditionally autoregressive process. In a design-based evaluation study, the proposed model-based estimators are shown to have smaller root-mean-square error and relative root-mean-square error than design-based estimators and multinomial model-based estimators. Supplementary materials accompanying this paper appear online.

Keywords: Generalized Dirichlet distribution; Spatial hierarchical model; Sampling variance modeling; Small area estimation; Survey statistics (search for similar items in EconPapers)
Date: 2018
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

Downloads: (external link)
http://link.springer.com/10.1007/s13253-018-0329-6 Abstract (text/html)
Access to the full text of the articles in this series is restricted.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:jagbes:v:23:y:2018:i:4:d:10.1007_s13253-018-0329-6

Ordering information: This journal article can be ordered from
http://www.springer.com/journal/13253

DOI: 10.1007/s13253-018-0329-6

Access Statistics for this article

Journal of Agricultural, Biological and Environmental Statistics is currently edited by Stephen Buckland

More articles in Journal of Agricultural, Biological and Environmental Statistics from Springer, The International Biometric Society, American Statistical Association
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().