This study reveals a nonparametric regression model for poverty indicators in Nusa Tenggara, highlighting the use of a mixed spline and kernel approach.
Key Points
The study identifies a multiresponse nonparametric regression model to analyze poverty indicators in Nusa Tenggara.
Findings report that the Human Development Index aligns with a truncated spline function, improving model accuracy.
Weighted least square estimation is employed to derive the best-fit model, achieving an R² value of 89.86%.
Implications suggest that mixed estimators are effective in modeling various poverty indicators across districts.