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Timbang Sirait
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Spatial Autoregressive Modeling on Linear Mixed Models for Dependency Between Regions Timbang Sirait
Aceh International Journal of Science and Technology Vol 12, No 1 (2023): April 2023
Publisher : Graduate Program of Syiah Kuala University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.13170/aijst.12.1.30403

Abstract

This study develops a linear mixed model (LMM) that includes spatial effects between regions with a spatial autoregressive model (SAR model). Between observations (regions) on that LMM are usually assumed to be independent. However, these assumptions are not always fulfilled due to dependency between regions. There are two important parts in spatial modeling: spatial dependence and spatial heterogeneity. In this study, we are concerned with the spatial lag or SAR models because dependency between variables of interest is easier to predict. On the other hand, all observations are real and can be directly seen from the data patterns. In addition, as a challenge for researchers to find all estimators while the values of the spatial dependence, sampling variance, and component variance are all unknown. This study aims to find all parameter estimators using a numerical approach and exact solutions. All exact estimators obtained are consistent estimators.
Spatial Autoregressive Modeling on Linear Mixed Models for Dependency Between Regions Timbang Sirait
Aceh International Journal of Science and Technology Vol 12, No 1 (2023): April 2023
Publisher : Graduate Program of Syiah Kuala University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.13170/aijst.12.1.30403

Abstract

This study develops a linear mixed model (LMM) that includes spatial effects between regions with a spatial autoregressive model (SAR model). Between observations (regions) on that LMM are usually assumed to be independent. However, these assumptions are not always fulfilled due to dependency between regions. There are two important parts in spatial modeling: spatial dependence and spatial heterogeneity. In this study, we are concerned with the spatial lag or SAR models because dependency between variables of interest is easier to predict. On the other hand, all observations are real and can be directly seen from the data patterns. In addition, as a challenge for researchers to find all estimators while the values of the spatial dependence, sampling variance, and component variance are all unknown. This study aims to find all parameter estimators using a numerical approach and exact solutions. All exact estimators obtained are consistent estimators.
Analisis Spasial Variabel-Variabel yang Memengaruhi Jumlah Kasus Baru HIV/AIDS di Provinsi Jawa Timur Tahun 2021 Safira Fauziana Thahar; Timbang Sirait
Seminar Nasional Official Statistics Vol 2023 No 1 (2023): Seminar Nasional Official Statistics 2023
Publisher : Politeknik Statistika STIS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34123/semnasoffstat.v2023i1.1602

Abstract

HIV/AIDS remains a global health emergency. In the last five years, East Java Province has always occupied the first position in the increase in the number of HIV/AIDS cases in Indonesia. The purpose of this study is to determine the variables that significantly affect the increase in the number of new HIV/AIDS cases in East Java Province in 2021 using the Geographically Weighted Negative Binomial Regression analysis method to overcome overdispersion and spatial effects on data. The independent variables studied were the percentage of condom users, population density, percentage of poor people, average years of schooling, percentage of villages with crimes of drug distribution and abuse, ratio of the number of health facilities per 10.000 population, and ratio of the number of health workers per 10.000 population. The data came from the publications of the Health Office and the Central Bureau of Statistics of East Java Province. The results showed that the distribution of the number of new HIV/AIDS cases in East Java in 2021 tended to cluster. In addition, four groups of districts/cities were formed based on the similarity of independent variables that had a significant effect.
Co-Authors Safira Fauziana Thahar