ScanZID: Spatial Scan Statistics with Zero Inflation and Dispersion

Max S. de Lima (), Luiz H. Duczmal (), José C. Neto (), Letícia P. Pinto (), Márcio A. C. Ferreira and Vanessa A. de Lima
Additional contact information
Max S. de Lima: Universidade Federal do Amazonas, Department of Statistics
Luiz H. Duczmal: Universidade Federal de Minas Gerais, Campus Pampulha, Department of Statistics
José C. Neto: Universidade Federal do Amazonas, Department of Statistics
Letícia P. Pinto: Universidade Federal de Minas Gerais, Department of Statistics
Márcio A. C. Ferreira: Universidade Federal do Amazonas, Department of Statistics
Vanessa A. de Lima: Universidade Federal do Amazonas, Department of Statistics

Chapter 27 in Handbook of Scan Statistics, 2024, pp 555-567 from Springer

Abstract: Abstract The spatial scan statistic is one of the most important methods to detect and monitor spatial disease clusters. Usually it is assumed that disease cases follow a Poisson, Binomial, Bernoulli, or negative binomial distribution. In practice, however, case count datasets frequently present zero inflation and/or dispersion (underdispersion or overdispersion), resulting in the violation of those commonly used models, thus increasing type I error occurrence. This paper describes the spatial scan statistic with the zero inflation and dispersion (ScanZID) to accommodate simultaneously the excess of zeroes and dispersion. The null and alternative model parameters are estimated by the expectation-maximization (EM) algorithm, and the p-value is obtained through the fast double bootstrap test. An application is presented for Hanseniasis data in the Brazilian Amazon.

Keywords: Spatial scan statistics; Zero inflated; Dispersion; EM algorithm (search for similar items in EconPapers)
Date: 2024
References: Add references at CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

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:sprchp:978-1-4614-8033-4_41

Ordering information: This item can be ordered from
http://www.springer.com/9781461480334

DOI: 10.1007/978-1-4614-8033-4_41

Access Statistics for this chapter

More chapters in Springer Books from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().