Titlebook: Numerical Linear Algebra for Applications in Statistics; James E. Gentle Textbook 1998 Springer Science+Business Media New York 1998 Analy

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書目名稱Numerical Linear Algebra for Applications in Statistics影響因子(影響力)




書目名稱Numerical Linear Algebra for Applications in Statistics影響因子(影響力)學(xué)科排名




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書目名稱Numerical Linear Algebra for Applications in Statistics被引頻次學(xué)科排名




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PACT

Solution of Linear Systems,ds. The system is said to be . if there exists such an ., and in that case a solution . may be written as .b, where . is some inverse of . If . is square and of full rank, we can write the solution as .b.

離開

Computation of Eigenvectors and Eigenvalues and the Singular Value Decomposition, . The matrix . is called the . of the polynomial .. It is easy to see that the characteristic equation of ., equation (2.11) on page 68, is the polynomial .(λ): . Thus, given a general polynomial ., we can form a matrix . whose eigenvalues are the roots of the polynomial. It is a well-known fact in

Proclaim

Applications in Statistics,data structured this way; the variables on the dataset generally correspond to the columns, and the observations correspond to the rows. If the data are in the matrix . a useful statistic is the sums of squares and cross-products matrix, ., or the “ adjusted” squares and cross-products matrix, where

SNEER

1431-8784 pplication require computations with vectors and matrices. This book describes accurate and efficient computer algorithms for factoring matrices, solving linear systems of equations, and extracting eigenvalues and eigenvectors. Although the book is not tied to any particular software system, it desc

RADE

Textbook 1998 require computations with vectors and matrices. This book describes accurate and efficient computer algorithms for factoring matrices, solving linear systems of equations, and extracting eigenvalues and eigenvectors. Although the book is not tied to any particular software system, it describes and

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錯誤

Solution of Linear Systems,ds. The system is said to be . if there exists such an ., and in that case a solution . may be written as .b, where . is some inverse of . If . is square and of full rank, we can write the solution as .b.