Modelling the number of HIV and aids cases in East Java using biresponse multipredictor negative binomial regression based on local linear estimator

Amin Tohari, Nur Chamidah, Fatmawati -, Budi Lestari

Abstract


A virus which attacks the CD4 lymphocytes of the immune system is called human immunodeficiency virus (HIV). If HIV is not addressed then the disease will develop into acquired immunodeficiency syndrome (AIDS). It means that HIV is the cause behind the AIDS infection. Indonesia has been classified into countries where HIV infection rates are high enough since 2006. East Java province was one of six other provinces in Indonesia entering endemic regions other than Jakarta, Papua, West Java, Riau and Bali. The our interest cases namely the number of HIV and AIDS cases in East Java, are two things that correlate with each other. They are categorized into discrete variables. Therefore, this study aims to model the our interest cases with both drug users and percentage of contraceptive users by using local linear Biresponse Multipredictor Negative Binomial (BMNB) regression model approach. By using maximum likelihood cross validation (MLCV) method, we obtain optimal bandwidth of first predictor variable (drug users) and second predictor variable (percentage of contraceptive users), i.e., 30 and 2.5, respectively. We get deviance values of 0.473 for local linear BMNB regression model approach and of 4.4822 for parametric regression model approach. It means that for modeling the our interest cases, the use of local linear BMNB regression model approach is better than the use of parametric regression model approach.

Full Text: PDF

Published: 2021-09-08

How to Cite this Article:

Amin Tohari, Nur Chamidah, Fatmawati -, Budi Lestari, Modelling the number of HIV and aids cases in East Java using biresponse multipredictor negative binomial regression based on local linear estimator, Commun. Math. Biol. Neurosci., 2021 (2021), Article ID 73

Copyright © 2021 Amin Tohari, Nur Chamidah, Fatmawati -, Budi Lestari. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Commun. Math. Biol. Neurosci.

ISSN 2052-2541

Editorial Office: office@scik.org

 

Copyright ©2021 CMBN