3.1 Least squares in matrix form BT - Econometric Methods with Applications in Business and EconomicsHeij, Christiaande Boer, PaulFranses, Philip HansKloek, Teunvan Dijk, Herman KHeij, C., De Boer, P., Franses, P. H., Kloek, T., & Van Dijk, H. K. (2004). Econometric M...
The solvability conditions for the inverseproblem AX = B in SRn×nP are obtained. The expression of the solution toProblem II is presented. 展开 关键词: matrix inverse problem least-squares solution DOI: 10.1300/J025v20n01_07 被引量: 37 ...
摘要: This paper considers the following problem: Problem A: find the least-squares solution of the some matrix equation over Hermitian anti-self unitary similar matrices. The general form of least-squares solutions is derived.关键词: Canonical correlation decomposition The least-squares solution ...
We consider the problem of finding the smallest adjustment to a given symmetric $n imes n$ matrix, as measured by the Euclidean or Frobenius norm, so that it satisfies some given linear equalities and inequalities, and in addition is positive semidefinite. This least-squares covariance adjustment...
=D.Analytical solution to the matrix equation is also derived.Furthermore,we apply this result to determine the least-squares symmetric and sub-antisymmetric solution ofthe matrix equation C~TXC=D with minimum-norm.Finally,some numerical results are reported to supportthe theories established in ...
We investigate matrix-free formulations for polynomialbased moving least-squares approximation. The well-known Shepard's method is one such formulation that leads to O(h) approximation order. We are interested in methods with higher approximation orders. Several possible approaches are identified, and ...
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,...
Matrix least-squares problems are ordinarily solved by QR factorization, and in the quasimatrix case, they are solved by quasimatrix QR factorization. This is the technology underlying the backslash operator described in the last section. A quasimatrix QR factorization takes this form: ...
The least-squares solutions of the matrix inverse problem for R-skew symmetric matrices with R* = R are firstly derived, then the solvability conditions ... Huang, G.-X.Yin, F.Chen, H.-F.Chen, L.Guo, K. - 《Applied Mathematics & Computation》 被引量: 0发表: 2010年 THE INVERSE PR...
By using the complex representations of quaternion matrices, Moore–Penrose generalized inverse and the Kronecker product of matrices, we derive the expression of the least squares Hermitian solution of the matrix equation ( A X B , C X D ) = ( E , F ) with the least norm over the skew...