统计研究 ›› 2019, Vol. 36 ›› Issue (6): 94-106.doi: 10.19343/j.cnki.11-1302/c.2019.06.008

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LMS方法及其在流量数据中的应用

苏宇楠 虞克明   

  • 出版日期:2019-06-25 发布日期:2019-06-13

LMS Method and Its Application for Streaming Data

Su Yunan & Yu Keming   

  • Online:2019-06-25 Published:2019-06-13

摘要: LMS模型是分析生长发育最常用的方法之一。本文详细阐述了LMS模型的构造原理;基于流量数据提出了费希尔信息矩阵与惩罚贝叶斯后验对数似然算法两种模型算法;利用中国健康营养调查(CHNS)1989-2011年中9年的流量数据,以所提出的LMS曲线算法为基础,通过计算BMI(Body Mass Index)绘制生长发育曲线研究我国青少年儿童生长发育情况和中年人健康问题。研究结果表明:1989-2011年间,我国0~18岁年龄段青少年儿童BMI中位数提高5%左右,生长发育高峰期有提前趋势;中年人群BMI中位数提高了10%左右,2000年后55周岁以上中年人体质差异有增大趋势。

关键词: Box-Cox变换, 年龄参考曲线, 惩罚贝叶斯后验似然

Abstract: The LMS model is one of the most commonly used methods for the growth pattern analysis. The structure principle of LMS model is described in detail and two model algorithms are proposed based on the Streaming Data. The Fisher Information Matrix and the Penalzied Bayesian Posterior Likelihood algorithm are proposed respectively by applying 9 years’ streaming data from 1989 to 2011 from Chinese Health Nutrition Survey (CHNS). Based on the proposed LMS curve algorithm, we calculate Body Mass Index (BMI) to draw the growth pattern curve to study the growth and development of children and adolescents and the health problems of middleaged people in China. The results show that in the 20 years around the 21st century, the median BMI of adolescents and children aged 0-18 in China has increased by about 5%.There is an advance trend in the peak period of growth and development. The median BMI of middleaged people has increased by 10 % approximately, and the difference of body constitution among middleaged people over 55 years old tends to increase after 2000.

Key words: Box-Cox Transformation, Age Reference Chart, Penalized Bayesian Posterior Likelihood