论文部分内容阅读
企业将资产运用于生产经营活动,并由此赚取更多的资产,即产生公司的收入.因此企业资产与收入之间必定存在一定的相关关系.在对上市公司总资产与营业收入进行一般线性拟合的基础之上,采用分位回归模型对上市公司的总资产与营业收入的关系进行深入剖析.结果表明,传统的线性模型只能揭示出总资产与营业收入呈正相关关系,而分位回归方法能更好地看出,高分位点营业收入的企业在提高一定总资产时,会更能促进营业收入的增长.由于收集到的数据中存在离群点,在第5节讨论了线性分位回归模型的统计诊断,类比于一般线性模型的R square得到不同分位点上的R square.通过删除离群点的处理,得出分位回归模型比一般线性模型更加稳健,数据在高分位点的拟合效果更好一些.
Enterprises use assets in production and business activities, and thus earn more assets, that is, the company’s revenue.Therefore, there must be some correlation between corporate assets and income.In the total assets of listed companies and operating income in general Based on the linear fitting, the quintile regression model is used to analyze the relationship between total assets and operating income of listed companies.The results show that the traditional linear model can only reveal the positive correlation between total assets and operating income, A bit regression method can better see that companies with higher-denominational point-of-sales revenues are more likely to boost revenue growth when they raise some total assets, as outliers are reported in the data collected in Section 5 The statistical diagnosis of the linear quantile regression model is similar to R square of the general linear model and R square of different quantiles is obtained. By removing the outlier, the quantile regression model is more stable than the general linear model. The data Fitting better at high scores.