Geographically weighted bivariate generalized Poisson regression: application to infant and maternal mortality data

Purhadi, Sutikno, Sarni Maniar Berliana*, Dewi Indra Setiawan

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

3 Citations (Scopus)

Abstract

Bivariate generalized Poisson regression (BGPR) is an extension of bivariate Poisson regression which deals overdipersion or underdispersion problem. This model gives global regression coefficients for all observations (locations) in the analysis. The BGPR model is then extended to take into account spatial heterogeneity, called geographically weighted bivariate generalized Poisson regression model, that yields varying regression coefficients locally. The regression model is applied to analyse factors affecting number of infant and maternal mortality in East Java, Indonesia.

Original languageEnglish
Pages (from-to)79-99
Number of pages21
JournalLetters in Spatial and Resource Sciences
Volume14
Issue number1
DOIs
Publication statusPublished - Apr 2021

Keywords

  • Count data
  • Spatial analysis
  • Spatial heterogeneity

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