Estimation of Mean Population in Small Area with Spatial Best Linear Unbiased Prediction Method

Syahril Ramadhan, Titin Siswantining, Saskya Mary Soemartojo

Research output: Contribution to journalConference articlepeer-review

2 Citations (Scopus)


Survey is aimed at estimating population parameters such as the total as well as the mean of an area with a large sample size. One approach in estimating population parameters are obtained through direct estimation methods. However, there is a problem when the direct estimation is used for a small area, which will cause a large standard error. This problem was addressed by developing a method of parameter estimation known as the Small Area Estimation (SAE) method. In this paper, we will describe the procedure to find the mean population estimate in a small area using Spatial Best Linear Unbiased Prediction (Spatial BLUP) method that follows Simultaneously Autoregressive (SAR) model. In general, this procedure begins with the definition of an area-level model. Then, the area-level model is expanded by the addition of spatial effect into the random effects of the area. In the end, the spatial model of the area level is used as the basis for estimating the mean population in small areas.

Original languageEnglish
Article number012043
JournalJournal of Physics: Conference Series
Issue number1
Publication statusPublished - 27 Nov 2017
EventInternational Conference on Science and Applied Science 2017, ICSAS 2017 - Surakarta, Indonesia
Duration: 29 Jul 2017 → …


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