摘要：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.
其他摘要：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.
关键词：Infant and Maternal Mortality rate; bivarite dependent; spline regression.
