Open AccessPengaruh Indeks Massa Tubuh dan TrigliseridaTerhadap Gula Darah dengan Model Regresi Nonparametrik Spline Biprediktor
Author(s) -
Dewi Rahma Ente,
Anna Islamiyati,
Raupong Raupong
Publication year - 2021
Publication title -
estimasi
Language(s) - English
Resource type - Journals
eISSN - 2721-3803
pISSN - 2721-379X
DOI - 10.20956/ejsa.v2i2.10262
Subject(s) - mathematics , statistics , nonparametric statistics , spline (mechanical) , regression analysis , single index model , linear regression , nonparametric regression , smoothing spline , engineering , structural engineering , bilinear interpolation , spline interpolation
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.