Least squares solutions of the matrix equation Formula Not Shown with the least norm for symmetric arrowhead matricesingentaconnectAPPLIED MATHEMATICS AND COMPUTATION -ELSEVIER-LiH.GaoZ.ZhaoD.
We will see in Section 16.3 that the accuracy of the solution using the normal equations depends on the square of condition number of the matrix. If κ (A) is large, the results can be seriously in error. 16.2.2 Using the QR Decomposition ...
1)least square approximation最佳平方逼近 1.In this paper , the authors analyzed the problem from the viewpoint of maximum entropy method and derived a practical formula based onleast square approximationprinciple and its algorithm.为此 ,对简便地产生概率密度函数的统一方法进行了研究 :分析了最大熵方法...
RegisterLog in Sign up with one click: Facebook Twitter Google Share on Facebook least-squares method (redirected fromleast squares) Also found in:Dictionary,Thesaurus,Medical,Acronyms,Wikipedia. least-squares method [¦lēst ′skwerz ‚meth·əd] ...
1、最小二乘法(Least squares method)The small square method (also known as the least square method) is a mathematical optimization technique. It matches the best function of finding the data by minimizing the squared error.Using the least square method, the unknown data can be obtained easily,...
The accuracy of the solution using the normal equations depends on the square of condition number of the matrix. If κ (A) is large, the results can be seriously in error. Solving Overdetermined Problems Using the QR Decomposition This is a time-honored technique for solving full-rank overdete...
least squares (PLS) is called the second generation regression method, because it can realize the comprehensive application of various data analysis methods. The main purpose of the principal component regression is to extract the relevant information hidden in the matrix X, and then used to ...
a non-linear programming model based on least square method is established.The ranked vector of the judgment matrix is obtained by solving the model.By using an expected value formula of triangular fuzzy number,the decision alternatives are ranked.Finally,a numerical example is given to prove the...
5.7 Rank Deficiency If X is rank deficient, or has more columns than rows, the square matrix XT X is singular and (XT X )−1 does not exist. The formula β = (XT X )−1XT y obtained from the normal equations breaks down completely. In these degenerate situations, the least ...
213), where r=vb(R) and vb(·) denotes the vectorizing operator taking the elements below the main diagonals of a square matrix, though the method is not dealt with in this article. Using the r×1 Lagrange multiplier vector ξρ as before with the q∗×1 vector ηρ=(θρ′,ξ...