REGRESI GENERALIZED POISSON UNTUK MEMODELKAN JUMLAH PENDERITA GIZI BURUK PADA BALITA DI SURABAYA

Mahfudhotin Mahfudhotin
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引用次数: 1

Abstract

The expansion of Poisson regression model which is used to solve the underdispersion data or overdispersion data known as Generalized Poisson (GP) regression model. The purpose of this final project is getting the parameter estimator of generalized linear model with response for GP  distribution using maximum likelihood. This GP regression model can be applied on the data of number of Marasmus Kwashiorkorpatients in 25 subdistrict in Surabaya city in 2010. The variable response is the number of Marasmus Kwashiorkor patients, where as the predictor responses are the number of people who married at early age , the number of family heads who not graduated elementary school, the number of children who participated posyandu, the number of medical , the number of visits BKIA, and the number of poor population .  The result of the GP regression model with statistic test can be concluded that the number of Marasmus Kwashiorkor patientsaffected by the number of visits BKIA and education levels of parents.The expansion of Poisson regression model which is used to solve the underdispersion data or overdispersion data known as Generalized Poisson (GP) regression model. The purpose of this final project is getting the parameter estimator of generalized linear model with response for GP  distribution using maximum likelihood. This GP regression model can be applied on the data of number of Marasmus Kwashiorkorpatients in 25 subdistrict in Surabaya city in 2010. The variable response is the number of Marasmus Kwashiorkor patients, where as the predictor responses are the number of people who married at early age , the number of family heads who not graduated elementary school, the number of children who participated posyandu, the number of medical , the number of visits BKIA, and the number of poor population .  The result of the GP regression model with statistic test can be concluded that the number of Marasmus Kwashiorkor patientsaffected by the number of visits BKIA and education levels of parents.
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POISSON的通病退行性回归,以模拟泗水学童营养不良的数量
广义泊松(GP)回归模型是对泊松回归模型的扩展,用于求解欠分散数据或过分散数据,称为广义泊松回归模型。本课题的目的是利用极大似然法求出GP分布的带响应广义线性模型的参数估计量。该GP回归模型可应用于泗水市2010年25个街道的夸希病患者人数数据。可变反应是消瘦症患者的数量,而预测反应是早婚人数、小学未毕业的户主人数、参加posyandu的儿童人数、医疗人数、BKIA访问人数和贫困人口人数。经统计检验的GP回归模型结果表明,轻度消瘦症患者数量受就诊次数和父母受教育程度的影响。广义泊松(GP)回归模型是对泊松回归模型的扩展,用于求解欠分散数据或过分散数据,称为广义泊松回归模型。本课题的目的是利用极大似然法求出GP分布的带响应广义线性模型的参数估计量。该GP回归模型可应用于泗水市2010年25个街道的夸希病患者人数数据。可变反应是消瘦症患者的数量,而预测反应是早婚人数、小学未毕业的户主人数、参加posyandu的儿童人数、医疗人数、BKIA访问人数和贫困人口人数。经统计检验的GP回归模型结果表明,轻度消瘦症患者数量受就诊次数和父母受教育程度的影响。
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