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Matrix Algebra for Applied Economics: Wiley Series in Probability and Statistics

Autor SR Searle
en Limba Engleză Hardback – 13 sep 2001
Coverage of matrix algebra for economists and students of economics

Matrix Algebra for Applied Economics explains the important tool of matrix algebra for students of economics and practicing economists. It includes examples that demonstrate the foundation operations of matrix algebra and illustrations of using the algebra for a variety of economic problems.

The authors present the scope and basic definitions of matrices, their arithmetic and simple operations, and describe special matrices and their properties, including the analog of division. They provide in-depth coverage of necessary theory and deal with concepts and operations for using matrices in real-life situations. They discuss linear dependence and independence, as well as rank, canonical forms, generalized inverses, eigenroots, and vectors. Topics of prime interest to economists are shown to be simplified using matrix algebra in linear equations, regression, linear models, linear programming, and Markov chains.

Highlights include:

  • Numerous examples of real-world applications
  • Challenging exercises throughout the book
  • Mathematics understandable to readers of all backgrounds
  • Extensive up-to-date reference material

Matrix Algebra for Applied Economics provides excellent guidance for advanced undergraduate students and also graduate students. Practicing economists who want to sharpen their skills will find this book both practical and easy-to-read, no matter what their applied interests.

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Specificații

ISBN-13: 9780471322078
ISBN-10: 0471322075
Pagini: 432
Dimensiuni: 156 x 234 x 26 mm
Greutate: 0.72 kg
Ediția:New.
Editura: Wiley
Seria Wiley Series in Probability and Statistics

Locul publicării:Hoboken, United States

Public țintă

Students of economics (upper–undergraduate and graduate–level) who need a strong background in matrix algebra or matrices, either as a basal text in a course on the subject matter or as a supplement in related areas (regression, linear programming, game theory, time series, Markov chains, etc); reference for practitioners who need a refresher.

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