Pengaruh Indeks Massa Tubuh dan TrigliseridaTerhadap Gula Darah dengan Model Regresi Nonparametrik Spline Biprediktor

  • Ente D
  • Islamiyati A
  • Raupong R
N/ACitations
Citations of this article
19Readers
Mendeley users who have this article in their library.

Abstract

The regression approach can be carried out using three approaches namely parametric, nonparametric and semiparametric approaches. Nonparametric regression is a statistical method used to see the relationship between the response variable and the predictor variable when the shape of the data curve is unknown. Diabetes mellitus (DM) or commonly called diabetes is a disease that is found and observed in various parts of the world today. DM is often marked by a significant increase in blood sugar levels. In this study using blood sugar levels as response variables, body mass index and triglycerides as predictor variables. Data were analyzed using truncated linear spline with one, two and three point knots experiments. The best model is obtained based on the minimum generalized cross validation (GCV) value. The results obtained that the best model is linear spline using three point knots.

Cite

CITATION STYLE

APA

Ente, D. R., Islamiyati, A., & Raupong, R. (2021). Pengaruh Indeks Massa Tubuh dan TrigliseridaTerhadap Gula Darah dengan Model Regresi Nonparametrik Spline Biprediktor. ESTIMASI: Journal of Statistics and Its Application, 71–79. https://doi.org/10.20956/ejsa.v2i2.10262

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free