REGRESSION NONPARAMETRIC SPLINE ESTIMATION ON BLOOD GLUCOSE OF INPATIENTS DIABETES MELLITUS AT SAMARINDA HOSPITAL

  • Ar Ruum Mia Sari Statistic Study Program, Faculty of Math and Science, Mulawarman University, Indonesia
  • Sifriyani Sifriyani Statistic Study Program, Faculty of Math and Science, Mulawarman University, Indonesia
  • Mohammad Nurul Huda Statistic Study Program, Faculty of Math and Science, Mulawarman University, Indonesia
DOI: https://doi.org/10.30598/barekengvol17iss1pp0147-0154
Keywords: Nonparametric Regression, Spline Truncated, Diabetes Mellitus, Knots, GCV

Abstract

This study used a biresponse nonparametric regression method with truncated spline estimation that used two response variables. Nonparametric regression method is used when the regression curve is not known for its shape and pattern.One of the nonparametric regression model approaches that is often used is the spline. The truncated spline approach has a segmented polynomial function that provides flexibility. The data used in the study were blood glucose levels in patients with diabetes mellitus, cholesterol levels, and triglyceride levels in 2020. From the results of the study, the best nonparametric biresponse spline truncated regression model with three knot points has been obtained where the minimum GCV value is  and has the an  value of  .

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Published
2023-04-16
How to Cite
[1]
A. Sari, S. Sifriyani, and M. Huda, “REGRESSION NONPARAMETRIC SPLINE ESTIMATION ON BLOOD GLUCOSE OF INPATIENTS DIABETES MELLITUS AT SAMARINDA HOSPITAL”, BAREKENG: J. Math. & App., vol. 17, no. 1, pp. 0147-0154, Apr. 2023.
Issue
Vol 17 No 1 (2023): BAREKENG: Journal of Mathematics and Its Applications
Section
Articles

Copyright (c) 2023 Ar Ruum Mia Sari, Sifriyani Sifriyani, Mohammad Nurul Huda

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