EN 
IN
Journal article
APLIKASI MODEL REGRESI SEMIPARAMETRIK SPLINE TRUNCATED (Studi Kasus Pasien Demam Berdarah Dengue (DBD) di Rumah Sakit Puri Raharja)
Ni Wayan Merry Nirmala Yani I Gusti Ayu Made Srinadi I Wayan Sumarjaya
Volume : 6 Nomor : 1 Published : 2017, January
E-JURNAL MATEMATIKA - Jurusan Matematika, Fakultas MIPA Universitas Udayana
Abstrak
Semiparametric regression is a regression model that includes parametric components and nonparametric components in a model. The regression model in this research is truncated spline semiparametric regression with case studies of patients with Dengue Hemorrhagic Fever (DHF) at Puri Raharja Hospital during the period of January to March 2015. The best regression model estimation is obtained from the selection of optimal knots which has minimum Generalized Cross alidation (GCV) is. Parametric components in this research include age (years), body temperature (0C), platelets ( ) and hematocrit (%) as a nonparametric component. The minimum value of GCV is 0.03552045 achieved at the point of 39.6 knots, MSE value of 0.0296922; and the value of coefficient determination is 98.91%, obtained from semiparametric regression model truncated linear spline (order 2) with a single point of knots. Keywords: GCV, knots, semiparametric regression, spline