APPLICATION OF THE PRAIS WINSTEN METHOD IN OVERCOMING AUTOCORRELATION ON LIFE EXPECTATION FACTORS

Hardian Bimanto, H. Notobroto, Soenarnatalina Melaniani
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引用次数: 0

Abstract

One of the error conditions that are required to be met is the absence of autocorrelation problems. Autocorrelation is a correlation of errors between observations, the existence of an error correlation between observations will cause deviations from the actual statistical value. One of the statistical methods for overcoming autocorrelation is the Prais Winsten method. This study aims to explain the Prais Winsten method in overcoming the problem of autocorrelation on factors that affect the life expectancy of East Java Province in 2018. This research is a secondary data analysis, data obtained from the East Java Province's health profile in 2018 with the dependent variable, namely life expectancy, and independent variables, namely prevalence of diarrhea, clean and healthy living behavior, and mean years of school. The results of this research indicated the finding of autocorrelation problems in the factors that affected the life expectancy of East Java Province in 2018. Improvements with the Prais Winsten method showed that the Durbin Watson value was at the critical point limit, Mean Square Error and coefficient of determination (R2) value was decreasing. This research concludes that the Prais Winsten method can overcome autocorrelation.
PRAIS-WINSTEN方法在克服寿命期望因子自相关中的应用
需要满足的误差条件之一是不存在自相关问题。自相关是观测值之间误差的相关性,观测值之间存在误差相关性会导致与实际统计值的偏差。克服自相关的统计方法之一是Prais-Winsten方法。本研究旨在解释Prais Winsten方法在克服影响东爪哇省2018年预期寿命的因素的自相关问题方面的作用。这项研究是一项二次数据分析,数据来自东爪哇省2018年的健康状况,因变量为预期寿命,自变量为腹泻患病率、清洁健康的生活行为和平均上学年限。这项研究的结果表明,在影响东爪哇省2018年预期寿命的因素中发现了自相关问题。对Prais-Winsten方法的改进表明,Durbin-WWatson值处于临界点极限,均方误差和决定系数(R2)值正在下降。本研究的结论是,Prais-Winsten方法可以克服自相关。
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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来源期刊
CiteScore
0.30
自引率
0.00%
发文量
12
审稿时长
12 weeks
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