Abstract
Maternal mortality and infant mortality rate is an interrelated issue. Therefore, maternal and infant mortality modeling can be done bivariate. One method used to model the relationship between response variables and predictor variables is regression. The regression approach that does not use the assumption is spline regression. Spline regression is a regression method based on spline function. Spline function is a polynomial piece that has high flexibility. In this study the response variable used is bivariate, the maternal mortality rate and infant mortality rate, while the predictor variable used is the percentage of slum households. The weighting used is based on the value of the covariance variant. Determination of point knots using Mean Square Error (MSE). The results obtained modeling maternal and infant mortality rates based on the percentage of slum households resulted inMAPE 55.55%. Number of knots obtained as much as 5 point knots with linear order.
Highlights
Multivariate statistics is statistical analysis methods that relate to more than one variable
Multivariate regression modeling gives the advantage one of which is a model that obtained more than one model in one analysis
The steps in spline truncated modeling include the determination of knots and order with Mean Square Error (MSE) followed by spline regression parameter estimation [4]
Summary
Multivariate statistics is statistical analysis methods that relate to more than one variable. Multivariate regression is a method to model the relationship between two or more dependent variables with some independent variables [1]. Regression modeling can be done by parametric and nonparametric approachs. One method of nonparametric regression approach is spline truncated regression. The development of multivariate spline modeling requires a weighted value. In the truncated spline modeling requires a knot point [3]. The steps in spline truncated modeling include the determination of knots and order with MSE followed by spline regression parameter estimation [4]. The maternal and infant mortality rate in Indonesia is decreasing every year. One of the factors causing increased maternal and infant mortality rates is environmental factors. In this study we will examine the model of maternal and infant mortality rate using spline bivariate regression. Environmental factors that made the independent variable is the percentage of slum households
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