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

机译:广义添加剂模型在婴儿死亡率数据中对p样分的应用

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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.
机译:婴儿死亡率(IMR)是反映人口健康状况的健康状况的指标。 2014年亚齐省期间的婴儿死亡率最高,与前4年相比,达到了15/1000的活产。广义添加剂模型(GAM)是可以处理响应变量不必正常分布的数据的条件的方法,并且与预测变量有关也不必是线性的。使用p样分底座的拟合Gam模型可以产生更平滑的曲线,并避免发生不充分的模型。 GAM P-SPLINE基础在本研究中的应用是2012 - 2015年亚历省IMR的数据次数。本研究的目的是通过GAM模型P-Spline基础获得最佳IMR的拟合模型。结果表明,GAM P样曲线的最佳模型可以在2012-2015期的IMR中解释,结7和GCV为0.0723。

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