局部补偿脊-地理加权回归模型在多重共线性空间数据中的应用(以东努沙登加拉省5岁以下儿童发育迟缓为例)

Alfi Fadliana, H. Pramoedyo, Rahma Fitriani
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引用次数: 2

摘要

根据2013年基线健康研究以及2016年和2017年营养状况调查的结果,东努沙登加拉省被记录为印度尼西亚发育迟缓发生率最高的省份。应努力制定与空间因素相结合的政策,以减少发育迟缓的发生率。LCR-GWR模型方法通过使用局部补偿脊来调整每个地区预测变量(即影响发育迟缓患病率的因素)之间共线性的影响。分析结果表明,影响东努沙登加拉省所有区/市发育迟缓患病率的因素是体重≥4倍的5岁以下儿童百分比、获得完全基本免疫接种的5岁以下儿童百分比、食用碘盐的家庭百分比、拥有体面饮用水来源的家庭百分比和实际人均支出。分析表明,LCR-GWR模型能较GWR模型更好地克服东努沙登加拉省发育不良的局部多重共线性问题,RMSE值(0.0344)低于GWR RMSE模型(3.8899)。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
IMPLEMENTATION OF LOCALLY COMPENSATED RIDGE-GEOGRAPHICALLY WEIGHTED REGRESSION MODEL IN SPATIAL DATA WITH MULTICOLLINEARITY PROBLEMS (Case Study: Stunting among Children Aged under Five Years in East Nusa Tenggara Province)
East Nusa Tenggara Province, according to the findings of 2013 Baseline Health Research and 2016 and 2017 Nutritional Status Surveys, was recorded as the province with the highest prevalence of stunting in Indonesia. Efforts should be made to formulate policies that are integrated with spatial aspects in order to reduce the prevalence of stunting. The LCR-GWR model approach is used by using locally compensated ridge, which were meant to adjusts to the effect of collinearity between predictor variables (i.e., the factors affecting the prevalence of stunting) in each area. Results of the analysis showed that factors affecting the prevalence of stunting in all districts/cities in East Nusa Tenggara Province are the percentage of children aged under five who were weighed ≥ 4 times, the percentage of children aged under five who receive complete basic immunization, the percentage of households consuming iodized salt, the percentage of households with decent source of drinking water and the real per capita expenditure. The analysis showed that LCR-GWR is able to produce a better model than the GWR model in overcoming local multicollinearity problems in stunting in East Nusa Tenggara Province, with lower RMSE value (0.0344) than the GWR RMSE model (3.8899).
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