样本相关矩阵

词组短语

sample correlation matrix

与样本相关矩阵相关的网络例句 [注：此内容来源于网络，仅供参考]

For these important and practical problems,sample covariance matrix is an important statistic because many important statistics are functionals of it.When we make statistical inferences,such as estimations and/or hypothesis tests,the sample covariance matrices must be investigated.

以上诸多方面在做估计和假设检验过程中，无不用到大维随机矩阵的处理，尤其是大维样本协方差矩阵的相关性质，因为多元分析中许多重要的统计量都可以表示成样本协方差矩阵的函数。

Five ways on comparing covariance matrix are applied to the Shanghai 50 Indexes Stock Exchange, which are sample covariance matrix, scalar matrix, two-parameter covariance matrix, single index matrix, constant correlation matrix. We adopt principal components method and Markowitz portfolio method to measure stock market risk using VaR, getting the effect of measuring market risk. The result shows that sample covariance matrix and two-parameter covariance matrix could measure market risk more effectively.

本文以上证50指数数据为样本，采用样本协方差矩阵、数量矩阵、两参数模型矩阵、单指数模型矩阵、常量相关矩阵作为与股票相关的协方差矩阵，结合投资策略选择的主成分方法和Markowitz最优投资组合方法，计算VaR以度量市场风险，并比较了五种协方差矩阵度量市场风险的效果，结果表明，在主成分方法中，样本协方差矩阵和两参数矩阵方法能有效的度量市场风险。

We follow the idea of sequential estimation method of Palandri (2007) but simplify the specification to estimate the correlations with BEKK specification proposing the Sequential-BEKK model using multistep Maximum likelihood estimation procedures to estimate.

通过运用BEKK模型模拟的数据，本文比较发现，Sequential-BEKK模型在进行样本内预测相关系数矩阵时，表现优于BEKK系列模型和OGARCH模型，稍差于CCC和Dec模型，但是Sequential-BEKK能够比其他模型更好的刻画相关系数的动态过程。

An on-line blind source separation algorithm of non-stationary mixed signals is presented. The algorithm uses the multiple time-delayed decorrelation and natural gradient rule to obtain the stationary point of the cost function, only a small number of observed samples is needed to minimize the Frobenius norm of the correlation matrices, so the computing cost is low and continuous separation calculation could be realized by on-line operation.

利用一种基于多时延解相关准则的代价函数和自然梯度原则，分别推导出非平稳信号在瞬态线性混合及卷积混合情况下的在线盲分离算法，仅通过对有限个时延样本的相关矩阵进行Frobenius范数最小化运算得到分离矩阵，计算工作量小，无需对样本进行分块处理，可实现对信号的连续跟踪操作。

与样本相关矩阵相关的网络解释 [注：此内容来源于网络，仅供参考]

sample correlation matrix：样本相关矩阵

sample correlation coefficient 样本相关系数 | sample correlation matrix 样本相关矩阵 | sample covariance 样本协方差

sample correlation matrix：样本相关矩阵,样本相关阵

sample correlation coefficient 样本相关系数 | sample correlation matrix 样本相关矩阵,样本相关阵 | sample covariance 样本协方差