搜索结果: 1-15 共查到“数学 Covariance”相关记录23条 . 查询时间(0.062 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
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2023/4/14
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
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
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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
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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
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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
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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...
Computation of the worst-case covariance for linear systems with uncertain parameters
Uncertain parameters of linear systems linear systems branch and bound algorithm is calculated
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2015/8/12
For a class of linear systems with unknown parameters that lie in intervals, we present a branch and bound algorithm for computing the worst-case covariance of the state.
Least-squares covariance matrix adjustment
Symmetric matrices linear equations inequalities the original matrix
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2015/8/10
We consider the problem of finding the smallest adjustment to a given symmetric n by n matrix, as measured by the Euclidean or Frobenius norm, so that it satisfies some given linear equalities and ine...
Sparse Covariance Estimation When Variables are Ordered
Sparse Covariance Estimation Variables Ordered
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2015/3/20
Sparse Covariance Estimation When Variables are Ordered.
Accounting for spatially varying directional effects in spatial covariance structures
Gaussian processes non-stationarity process convolution projection
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2012/11/23
Wind direction plays an important role in the spread of pollutant levels over a geographical region. We discuss how to include wind directional information in the covariance function of spatial models...
Asymptotic properties of robust complex covariance matrix estimates
Asymptotic properties robust complex covariance matrix estimates
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2012/11/22
In many statistical signal processing applications, the estimation of nuisance parameters and parameters of interest is strongly linked to the resulting performance. Generally, these applications deal...
Two sample tests for high-dimensional covariance matrices
High-dimensional covariance large p small n likelihood ratio test testing for gene-sets
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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...
Robust Maximization of Asymptotic Growth under Covariance Uncertainty
Robust Maximization of Asymptotic Growth Covariance Uncertainty Portfolio Management
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2011/10/8
Abstract: This paper resolves a question proposed in Kardaras and Robertson (2011): how to invest in a robust growth-optimal way in a market where precise knowledge of the covariance structure of the ...
An Efficient Algorithm for Maximum-Entropy Extension of Block-Circulant Covariance Matrices
Efficient Algorithm Maximum-Entropy Extension Block-Circulant Covariance Matrices Optimization and Control
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2011/9/5
Abstract: This paper deals with maximum entropy completion of partially specified block-circulant matrices. Since positive definite symmetric circulants happen to be covariance matrices of stationary ...
On the Equivalence of the General Covariance Union (GCU) and Minimum Enclosing Ellipsoid (MEE) Problems
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2011/2/24
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
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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...