TY - JOUR
T1 - Geographically weighted bivariate generalized Poisson regression
T2 - application to infant and maternal mortality data
AU - Purhadi,
AU - Sutikno,
AU - Berliana, Sarni Maniar
AU - Setiawan, Dewi Indra
N1 - Publisher Copyright:
© 2021, The Author(s), under exclusive licence to Springer-Verlag GmbH, DE part of Springer Nature.
PY - 2021/4
Y1 - 2021/4
N2 - 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.
AB - 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.
KW - Count data
KW - Spatial analysis
KW - Spatial heterogeneity
UR - http://www.scopus.com/inward/record.url?scp=85104214842&partnerID=8YFLogxK
U2 - 10.1007/s12076-021-00266-5
DO - 10.1007/s12076-021-00266-5
M3 - Article
AN - SCOPUS:85104214842
SN - 1864-4031
VL - 14
SP - 79
EP - 99
JO - Letters in Spatial and Resource Sciences
JF - Letters in Spatial and Resource Sciences
IS - 1
ER -