Spline Regression Analysis to Modelling The Open Unemployment Rate in Sulawesi

Selvia Anggun Wahyuni, R. Ratnawati, I. Indriyani, M. Fajri
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引用次数: 3

Abstract

Unemployment is a very complex problem because it affects and is influenced by several factors that interact with each other following a pattern that is not always easy to understand. If unemployment is not immediately addressed, it can cause social vulnerability and potentially lead to poverty. This research will use the spline regression method in modeling the 2018 Sulawesi open unemployment rate. The results obtained are the best spline model obtained from the optimum knots point with a combination of knots 3,3,1,1,3,3. This model has the minimum GCV value 1,97 with R2 77,67%. All variables significantly influence the open unemployment rate.
苏拉威西岛公开失业率的样条回归分析
失业是一个非常复杂的问题,因为它影响并受几个因素的影响,这些因素按照一种并不总是容易理解的模式相互作用。如果不立即解决失业问题,它可能造成社会脆弱性,并可能导致贫困。本研究将采用样条回归方法对2018年苏拉威西岛公开失业率进行建模。得到的结果是从结点3,3,1,1,3,3的最优结点组合得到的最佳样条模型。该模型的最小GCV值为1.97,R2为77.67%。所有变量都显著影响公开失业率。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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