搜索结果: 1-15 共查到“理学 Covariance”相关记录68条 . 查询时间(0.109 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...
A FRAMEWORK FOR POSITION UNCERTAINTY OF UNORGANISED THREE-DIMENSIONAL POINT CLOUDS FROM NEAR-MONOSTATIC LASER SCANNERS USING COVARIANCE ANALYSIS
Position uncertainty Three-dimensional Point Cloud Laser Scanning
2015/8/13
Position uncertainty is one of the most important quantities of an unorganised three-dimensional point clouds since it
provides the confidence level of any parametric estimation such as surface...
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
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
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
2015/3/20
Sparse Covariance Estimation When Variables are Ordered.
We analyse the flux power spectrum and its covariance using simulated Lyα forests. We find that pseudo-hydro techniques are good approximations of hydrodynamical simulations at high redshift. However,...
Incorporating grassland management in ORCHIDEE: model description and evaluation at 11 eddy-covariance sites in Europe
Incorporating grassland management ORCHIDEE
2014/12/12
This study describes how management of grasslands is included in the Organizing Carbon and Hydrology in
Dynamic Ecosystems (ORCHIDEE) process-based ecosystem model designed for largescale application...
Impact of a time-dependent background error covariance matrix on air quality analysis
Surface of assimilation system analysis of ozone the covariance matrix data assimilation system physical state
2014/12/10
In this article we study the influence of different characteristics of our assimilation system on surface ozone analyses over Europe. Emphasis is placed on the evaluation of the background error covar...
Construction of non-diagonal background error covariance matrices for global chemical data assimilation
Chemical data assimilation To optimize the noise Model predictions Chemical state
2014/12/9
Chemical data assimilation attempts to optimally use noisy observations along with imperfect model predictions to produce a better estimate of the chemical state of the atmosphere. It is widely accept...
Accounting for spatially varying directional effects in spatial covariance structures
Gaussian processes non-stationarity process convolution projection
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
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...
