SA  >> Vol. 4 No. 3 (September 2015)

    变量选择方法在多重共线性问题中的应用—基于全国科技投入产出数据的实例
    The Application of Variable Selection to Multi-Collinearity Problems—Based on the Research and Development Input and Output Data

  • 全文下载: PDF(539KB) HTML   XML   PP.133-143   DOI: 10.12677/SA.2015.43015  
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作者:  

安蕾,贾慧芝:云南财经大学统计与数学学院,云南 昆明

关键词:
变量选择多重共线性岭回归PLS回归Variable Selection Multi-Collinearity Ridge Regression Partial Least-Squares regression

摘要:

科研投入是提升一国创新能力的前提,但指标之间往往存在较强的多重共线性问题。本文使用岭回归、PLS回归的方法,把我国31个主要的省市自治区分为两类,依次构建R&D投入–产出模型,以期了解我国R&D投入模式。研究结果表明,不同地区受科技投入指标的影响不同,中西部发展地区受政府及企业投入的影响都很显著,而经济较为发达的省市企业的科技创新意识更强。

A prerequisite for the promotion of a nation’s innovation ability is the input of scientific research, but there are always many multi-collinearity problems among the indexes. In order to know the R&D input-output mode, 31 provinces are divided into two parts to set up ridge regression and PLS regression models separately. The research results show that different areas are influenced by different factors. The Midwest is susceptible to the input of the government and companies, while the technological innovation consciousness of the enterprises in the developed area is stronger.

文章引用:
安蕾, 贾慧芝. 变量选择方法在多重共线性问题中的应用—基于全国科技投入产出数据的实例[J]. 统计学与应用, 2015, 4(3): 133-143. http://dx.doi.org/10.12677/SA.2015.43015

参考文献

[1] Griliches, Z. (1979) Issues in assessing the contribution of R&D to productivity growth. Bell Journal of Economics, 10, 92-116.
http://dx.doi.org/10.2307/3003321
[2] Griliches, Z. (1981) Market value, R&D, and patents. Economics Letters, 7, 183-187.
http://dx.doi.org/10.1016/0165-1765(87)90114-5
[3] Hitt, M.A., Hosdisson, R.E., Johnson, R.A. and Moesel, D.D. (1996) The market for corporate control and firm innovation. Academy of Management Journal, 39, 1084-1119.
http://dx.doi.org/10.2307/256993
[4] Inonu, E. (2003) The influence of cultural factors on scientific production. Scientometrics, 56, 137-146.
http://dx.doi.org/10.1023/A:1021906925642
[5] 余昕, 王冬, 韩楠, 王欣 (2007) 发达国家科技投入效率初探. 科技进步与对策, 8, 129-131.
[6] 李燕萍, 郭玮, 黄霞 (2009) 科研经费的有效使用特征及其影响因素. 科学研究, 11, 1685-1691.
[7] 华锦阳, 汤丹 (2010) 科技投入机制的国际比较及对我国科技政策的建议. 科技进步与对策, 5, 25-30.
[8] 吴喜之 (2012) 复杂数据统计方法. 中国人民大学出版社, 北京, 25-29.
[9] 王惠文 (1999) 偏最小二乘回归方法及应用. 国防工业出版社, 北京, 151-152.
[10] 齐琛, 方秋莲 (2013) 偏最小二乘建模在R软件中的实现及实证分析. 数学理论与应用, 2, 104-105.
[11] Miller, R.G. (1974) An unbalanced jackknife. The Annals of Statistics, 2, 880-891.
http://dx.doi.org/10.1214/aos/1176342811