两种成分数据预测建模方法的比较研究

基金项目: 北京市自然科学基金资助项目(9002002)

详细信息

Contrastive Study on Two Forecast Modeling Methods of Compositional Data

School of Economics and Management, Beijing University of Aeronautics and Astronautics, Beijing 100083, China

摘要: 在社会、经济、技术等领域中,成分数据是一种被广泛应用的数据类型。文章对两种不同的成分数据预测建模方法进行对比研究:一种是利用对数变换对成分数据进行预测的建模方法;另一种是利用球面投影,通过对成分数据的非线性降维,得到建立预测模型的方法。通过比较研究,指出两种方法在应用方面的优缺点,并且利用北京市按所有制划分的从业人员数据,应用两种方法分别进行预测,对北京市的就业情况进行简要分析。
- 成分数据 /
- 预测模型 /
- 比较研究
Abstract: Compositional data are widely used in the field of society, economy and technology. This paper discusses two different forecast modeling methods of compositional data .The first method supplies a forecast model making use of logarithm change. Sphere projection, a non-linear approach for dimensionality deduction, is used in the second method to build a forecast model. With the contrastive study, the paper lists out the advantage and disadvantage of each. The methods talked above are respectively used in the compositional data of the Beijing employees from 1994 to 2000 that are divided by proprietorship. In the end of this paper, the status of employment in Beijing is analyzed.
- compositional data /
- forecast model /
- contrastive study

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