搜索结果: 1-9 共查到“数理统计学 Covariance”相关记录9条 . 查询时间(0.078 秒)
Academy of Mathematics and Systems Science, CAS Colloquia & Seminars：Best subset selection via distance covariance
距离协方差 最佳子集 回归分析
2023/4/14
Best subset selection is an important problem in regression analysis,which has many applications in computer science and medicine. However, the existing best subset selection methods have some limitat...
中山大学岭南学院高级计量经济学课件（II：Panel Data）CH3 Covariance Structure and Robust Covariance Estimation
中山大学岭南学院 高级计量经济学 课件（II：Panel Data） CH3 Covariance Structure and Robust Covariance Estimation
2017/6/14
中山大学岭南学院高级计量经济学课件（II：Panel Data）CH3 Covariance Structure and Robust Covariance Estimation。
昆明理工大学理学院概率论与数理统计课件Chapter 4 The Expectation and Variance--Covariance&Correlation
昆明理工大学理学院 概率论与数理统计 课件 Chapter 4 The Expectation and Variance Covariance&Correlation
2017/4/17
昆明理工大学理学院概率论与数理统计课件Chapter 4 The Expectation and Variance--Covariance&Correlation.
Sparse inverse covariance estimation with the lasso
Sparse inverse covariance estimation the lasso
2015/8/21
We consider the problem of estimating sparse graphs by a lasso penalty applied to the inverse covariance matrix. Using a coordinate descent procedure for the lasso, we develop a simple algorithm— the ...
Exact Covariance Thresholding into Connected Components for Large-Scale Graphical Lasso
sparse inverse covariance selection sparsity graphical lasso Gaussian graphical models graph connected components concentration graph large scale covariance estimation
2015/8/21
We consider the sparse inverse covariance regularization problem or graphical lasso with regularization parameter λ. Suppose the sample covariance graph formed by thresholding the entries of the sampl...
Sparse Covariance Estimation When Variables are Ordered
Sparse Covariance Estimation Variables Ordered
2015/3/20
Sparse Covariance Estimation When Variables are Ordered.
Two sample tests for high-dimensional covariance matrices
High-dimensional covariance large p small n likelihood ratio test testing for gene-sets
2012/6/21
We propose two tests for the equality of covariance matrices between two high-dimensional populations. One test is on the whole variance--covariance matrices, and the other is on off-diagonal sub-matr...
In this paper we describe General Covariance Union (GCU) and show that solutions to GCU and the Minimum Enclosing Ellipsoid (MEE) problems are equivalent.
Control of the False Discovery Rate Under Arbitrary Covariance Dependence
Rate Covariance Dependence
2011/1/4
Multiple hypothesis testing is a fundamental problem in high dimensional inference, with wide applications in many scientific fields. In genome-wide association studies, tens of thousands of tests are...