空间加权矩阵在空间实证最佳线性非加权预测模型中与 "权力 "和 "女王 "的比较(2019 年东爪哇省人均支出研究)

Luthfatul Amaliana, Andi Prasetya
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引用次数: 0

摘要

本研究旨在对 SEBLUP 模型中的权力和皇后空间加权矩阵进行比较,以估算 2019 年东爪哇的人均支出。使用的数据是二手数据,然后通过空间经验最佳线性无偏预测(SEBLUP)对数据进行分析。研究结果表明,使用 SEBLUP 模型估算东爪哇人均支出的最佳空间加权矩阵是 Queen 空间加权矩阵,因为它产生的 MSE 值最小。在本研究中,对东爪哇省人均支出有显著影响的因素包括人口密度(X1)、医疗设施数量(X2)、公立小学数量(X3)以及将 BPJS 作为基金援助对象的居民比例(X5)。本研究的新颖之处在于将已证明对人均支出有重大影响的多个决定因素结合起来,并将重点放在中等规模的地区(16 个)。
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COMPARISON OF SPATIAL WEIGHTED MATRIX BETWEEN POWER AND QUEEN ON THE SPATIAL EMPIRICAL BEST LINEAR UNBIASED PREDICTION MODEL (Study on Per Capita Expenditure in East Java Province in 2019)
This study aims to make a comparison related to the spatial weighted matrix of power and queen in the SEBLUP model to estimate per capita expenditure in East Java in 2019. The data used is secondary data then the data were analyzed by the Spatial Empirical Best Linear Unbiased Prediction (SEBLUP). The results of this study indicate that the best spatial weighted matrix for estimating per capita expenditure in East Java using the SEBLUP model is the spatial weighted matrix of Queen, because it produces the smallest MSE value. In this study, the factors that significantly affect East Java's per capita expenditure are population density (X1), number of health facilities (X2), number of public elementary schools (X3), and the percentage of residents who have BPJS as the Fund Assistance Recipients (X5). The novelty of this study are combining multiple determinant factors that have demonstrated their substantial/significant effect on the average per capita expenditure and focusing on the regions characters in intermediate size (16
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