Application of generalized additive models with P-Spline basis for infant mortality rate data

8th Annual International Conference 2018 on Science and Engineering

工业技术（总论）

Ahya, D.^1 ; Miftahuddin^1

Department of Statistics, Faculty of Mathematics and Sciences, Syiah Kuala University, Banda Aceh

23111, Indonesia^1

关键词: Best model;    Fitting model;    Generalized additive model;    Health status;    Infant mortality rates;    P-splines;    Predictor variables;   

Others  :  https://iopscience.iop.org/article/10.1088/1757-899X/523/1/012004/pdf
DOI  :  10.1088/1757-899X/523/1/012004

学科分类：工业工程学

来源: IOP

【 摘 要 】

Infant Mortality Rate (IMR) is an indicator of health that reflects the state of the health status of a population. The infant mortality rate in Aceh province period of 2014 has the highest position compared to the previous 4 years that amounted to 15/1000 live births. Generalized Additive Models (GAM) is a method that can handle the condition of the data which response variable does not have to be normally distributed and related with the predictor variable also does not have to be linear. Fitting GAM models with P-spline base can produce a smoother curve and avoid the occurrence of misfitting models. Application of GAM P-spline bases in this research is used data number of IMR in Aceh province period of 2012-2015. The purpose of this research is to get the best fitting model of IMR with GAM models P-spline bases. The results show that the best model of GAM P-spline which can be explain IMR in Aceh Province period of 2012-2015 with knots 7 and GCV is 0,0723.