Variance decomposition, also known as factor analysis or decomposition of variance, is a statistical technique used to break down the overall variance of a variable into its individual components. This method is commonly applied in various fields such as economics, finance, and biology to understand the relative contribution of different factors to the total variance. In economics, variance decomposition is often used to analyze the sources of economic fluctuations, while in finance, it helps to assess the risk factors affecting investment returns. In biology, it is utilized to study the variation in biological traits and their underlying determinants. By understanding the factors contributing to variance, researchers can gain valuable insights into the underlying mechanisms driving complex systems. Here are some examples of how variance decomposition has been used in different disciplines to elucidate the sources of variation and their impact on the overall system.
方差分解,variance decomposition
variance decomposition proportion方差分解比
1.In this paper,a new method based on condition index andvariance decomposition proportion(CIVDP) is proposed to diagnose the presence,number and composition of multicollinearities which exist among the columns of the design matrix in Gauss-Markov model for surveying adjustment.运用条件指标和方差分解比提出一种诊断设计阵复共线性的新方法———条件指标-方差分解比(CIVDP)法,该方法不但可以确定设计阵数据列之间复共线性关系的个数,而且可以确定每个复共线性关系存在于哪些数据列之间,并通过大量的模拟计算和实际应用验证该方法的有效性。
3)Hasbrouck Variance DecomposeHasbrouck方差分解
4)bias/variance decomposition偏差/方差分解
1.The selection of learning algorithms in meta-learning is investigated from the point ofbias/variance decomposition as well as the effect of correlation on its accuracy.提出一种元学习定义,从偏差/方差分解角度对元学习中学习算法的选取机制进行研究,得出了元级选用错误率低且偏差小的学习算法、基级学习算法按照错误率及方差从低到高排列的结论。
5)Variance decomposition analysis方差分解分析
6)variance decomposition预测方差分解
1.On the foundation of vector auto regression model,this paper identifies the long run equal relationship and the short run dynamic relationship,applies impulse response function andvariance decomposition to make up empirical analysis,which refers to volatility of equipment manufacturing profit in Liaoning.通过建立VAR模型,运用脉冲响应函数和预测方差分解的方法对辽宁省装备制造业利润增长的波动情况进行实证分析。
2.Based on vector autoregressions(VAR) model,this paper measures the length of the impact lags of China’s financial policy by using impulse response function andvariance decomposition comparatively and cross correlation.基于向量自回归模型 ,本文利用脉冲响应函数和预测方差分解方法对我国金融政策的作用时滞做了具体测算。
3.On the basis of explaining the effective theory and the transmission mechanism theory of monetary policy, by adopting cointegration test, vector autoregressive model(VAR) andvariance decomposition, this paper has conducted an empirical study on the controversy monetary transmission mechanism of China with the data sample from 1984 to .本文在详细阐述货币政策有效性理论和货币政策传导机制理论的基础上，运用协整检验、向量自回归和预测方差分解等方法，围绕国内外学者争议较多的货币渠道和信贷渠道，对我国1984—的货币政策传导机制进行实证分析。
延伸阅读
并合方差分子式：CAS号：性质：是按加权方式计算出的各组的共同方差，当试验分m组进行，总的测定方差s2由m组的方差si2(i=1,2, …,m)共同决定。总方差，式中ni、fi和xi；分别为第i组的测定次数、自由度和平均值，xij是第i组的第j次测定值。
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