Implementing GCV and mGCV to Determine Optimal Knot in Spline Regression for East Java Life Expectancy
Keywords:
Generalized Cross Validation, Life Expectancy, Modified Generalized Cross Validation, Nonparametric Spline RegressionAbstract
Life Expectancy is a vital indicator for evaluating population’s overall welfare and health status within a specific region. According to data published by Badan Pusat Statistik (BPS) National, East Java Province ranks 10th nationally in terms of life expectancy in 2024, with male life expectancy recorded at 70.39 years and female life expectancy at 74.4 years. This research focuses on examining four key factors that are believed to influence life expectancy in East Java during the 2024 including the Percentage of the Poor Population (X1), the Percentage of Individuals Aged 5 and Above Who Regularly Smoke Tobacco (X2), the Expected Years of Schooling (X3), and the Open Unemployment Rate (X4). To determine the optimal knot points in the nonparametric truncated spline regression model, the study utilizes Generalized Cross-Validation (GCV) and the modified Generalized Cross-Validation (mGCV) methode by minimizing their respective error values. The findings indicate that all four variables significantly impact life expectancy. Among the methods applied, the mGCV approach demonstrates good performance, achieving the lowest error value of 0.100 and a coefficient of determination of 82.91%.
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