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Model Regresi Bivariate Zero-Inflated Poisson Pada Kematian Ibu dan Bayi

ESTIMASI: Journal of Statistics and Its Application · Vol. 3 No. 1 (2022) · pp. 33–40

DOI
10.20956/ejsa.vi.11557
ISSN
2721-379X, 2721-3803
Published
2022-02-01
Publisher
Hasanuddin University
Language
en

Abstract

Overdispersion is a condition with greater variance than the mean. One of the causes overdispersion is more zero-value observations so the Zero-Inflated Poisson (ZIP) regression model can be used. As for modeling a pair of discrete data is correlated and overdispersion, it can be used the Bivariate Zero-Inflated Poisson (BZIP) regression model. The BZIP regression model is a model with response variables with mixed distributions between Bivariate Poisson distribution and a point probability at (0,0). Parameters of the BZIP regression model are estimated using maximum likelihood estimation (MLE) with expectation maximization (EM) algorithm. This research was applied to data on number of maternal and infant mortality in the city of Makassar in 2017. The result obtained is the AIC value of the BZIP regression model is 170.976 smaller than the Bivariate Poisson regression model is 198.120. This shows that the BZIP regression model is better used for data with overdispersion.

Keywords

Collaboration network of the authors

40 authors · 90 co-authorship links · showing the 40 most connected

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  • Sultan Ageng Tirtayasa University
  • Affiliation unknown
  • Different organisations
  • Same organisation
  • Affiliation unknown
  • Thicker line = more joint articles · bigger circle = more articles
Show as table
Co-authorOrganisationJoint articles
Erna Tri HerdianiAffiliation unknown4
Sitti SahrimanAffiliation unknown4
Nirwan IlyasAffiliation unknown3
Nasrah SirajangAffiliation unknown3
RaupongAffiliation unknown2
La Podje TalangkoAffiliation unknown2
Anisa AnisaSultan Ageng Tirtayasa University2
Nurtiti SunusiAffiliation unknown2
Rusydah KhaeratiAffiliation unknown1
Grace Oktavia YusufAffiliation unknown1
Iis Cendrah KasihAffiliation unknown1
Ika FitrianaAffiliation unknown1
Asti Inayati MagfirahAffiliation unknown1
Mega Selvia TjahayaAffiliation unknown1
Fitriatusakiah FitriatusakiahAffiliation unknown1
Raupong RaupongAffiliation unknown1
Andi Tenri Riski AmaliaAffiliation unknown1
Najiha AlimatunAffiliation unknown1
Reski AmalahAffiliation unknown1
Nur Alfianingsih RajaAffiliation unknown1
Nur Fuadil Maqnun WahabAffiliation unknown1
Nurtit SunusiAffiliation unknown1
Aqilah Salsabila RahmanAffiliation unknown1
Ainul FajriAffiliation unknown1
Anisa Haura Salsa Fatih YusufAffiliation unknown1
Ika Pratiwi HayaAffiliation unknown1
Nurhidaya LAffiliation unknown1
Anna IslamiyatiAffiliation unknown1
Andi Ummi Melin Aicha AichaAffiliation unknown1
Hendriete Tiur Marowi WaibusiAffiliation unknown1
Victor LimanAffiliation unknown1
Sonya SonyaAffiliation unknown1
Anisa KalondengAffiliation unknown1
Surya Cahyadi SyamAffiliation unknown1
Wa Ode Sitti Amni AmniAffiliation unknown1
Amalia AndrianingrumAffiliation unknown1
Rini JamalAffiliation unknown1

Affiliations come from OpenAlex; journal OAI-PMH metadata carries none. Authors without an OpenAlex ID are matched by name, which can merge or split people.

Metadata source: OAI-PMH (metadata jurnal) https://journal.unhas.ac.id/index.php/ESTIMASI/oai, first harvested 2 Nov 2026, last seen 2 Nov 2026.
Original metadata (oai_dc) 
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	<dc:title xml:lang="en">Model Regresi Bivariate Zero-Inflated Poisson Pada Kematian Ibu dan Bayi</dc:title>
	<dc:creator xml:lang="en">Yunita, Andi Isna</dc:creator>
	<dc:creator xml:lang="en">Jaya, Andi Kresna</dc:creator>
	<dc:creator xml:lang="en">Tinungki, Georgina Maria</dc:creator>
	<dc:subject xml:lang="en">BZIP Regression</dc:subject>
	<dc:subject xml:lang="en">Infant Mortality</dc:subject>
	<dc:subject xml:lang="en">Maternal Mortality</dc:subject>
	<dc:subject xml:lang="en">Overdispersion</dc:subject>
	<dc:description xml:lang="en">Overdispersion is a condition with greater variance than the mean. One of the causes overdispersion is more zero-value observations so the Zero-Inflated Poisson (ZIP) regression model can be used. As for modeling a pair of discrete data is correlated and overdispersion, it can be used the Bivariate Zero-Inflated Poisson (BZIP) regression model. The BZIP regression model is a model with response variables with mixed distributions between Bivariate Poisson distribution and a point probability at (0,0). Parameters of the BZIP regression model are estimated using maximum likelihood estimation (MLE) with expectation maximization (EM) algorithm. This research was applied to data on number of maternal and infant mortality in the city of Makassar in 2017. The result obtained is the AIC value of the BZIP regression model is 170.976 smaller than the Bivariate Poisson regression model is 198.120. This shows that the BZIP regression model is better used for data with overdispersion.</dc:description>
	<dc:publisher xml:lang="en">Hasanuddin University</dc:publisher>
	<dc:date>2022-02-01</dc:date>
	<dc:type>info:eu-repo/semantics/article</dc:type>
	<dc:type>info:eu-repo/semantics/publishedVersion</dc:type>
	<dc:format>application/pdf</dc:format>
	<dc:identifier>https://journal.unhas.ac.id/index.php/ESTIMASI/article/view/11557</dc:identifier>
	<dc:identifier>10.20956/ejsa.vi.11557</dc:identifier>
	<dc:source xml:lang="en">ESTIMASI: Journal of Statistics and Its Application; Vol. 3, No. 1, Januari, 2022 : Estimasi; 33-40</dc:source>
	<dc:source>2721-379X</dc:source>
	<dc:source>2721-3803</dc:source>
	<dc:language>en</dc:language>
	<dc:relation>https://journal.unhas.ac.id/index.php/ESTIMASI/article/view/11557/7854</dc:relation>
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