Linear Algebra and Linear Models - Brossura

Bapat, Ravindra B. B.

Brossura

ISBN 10: 1447127382 ISBN 13: 9781447127383

Casa editrice: Springer, 2012

Riassunto

Linear Algebra and Linear Models comprises a concise and rigorous introduction to linear algebra required for statistics followed by the basic aspects of the theory of linear estimation and hypothesis testing. The emphasis is on the approach using generalized inverses. Topics such as the multivariate normal distribution and distribution of quadratic forms are included.

For this third edition, the material has been reorganised to develop the linear algebra in the first six chapters, to serve as a first course on linear algebra that is especially suitable for students of statistics or for those looking for a matrix theoretic approach to the subject. Other key features include:

coverage of topics such as rank additivity, inequalities for eigenvalues and singular values;

a new chapter on linear mixed models;

over seventy additional problems on rank: the matrix rank is an important and rich topic with connections to many aspects of linear algebra such as generalized inverses, idempotent matrices and partitioned matrices.

This text is aimed primarily at advanced undergraduate and first-year graduate students taking courses in linear algebra, linear models, multivariate analysis and design of experiments. A wealth of exercises, complete with hints and solutions, help to consolidate understanding. Researchers in mathematics and statistics will also find the book a useful source of results and problems.

Su questo libro

Informazioni sull?autore

Felix Bronner, PhD is Professor Emeritus at University of Connecticut Health Center, Farmington, CT, USAMary Farach-Carson, PhD is Associate Vice Provost for Research Professor of Biochemistry and Cell Biology at Rice University, Houston, TX, USA.Helmtrud I. Roach, PhD was a Reader in the Bone and Joint Research Group at Southampton General Hospital, Southampton, UK.

Dalla quarta di copertina

Linear Algebra and Linear Models comprises a concise and rigorous introduction to linear algebra required for statistics followed by the basic aspects of the theory of linear estimation and hypothesis testing. The emphasis is on the approach using generalized inverses. Topics such as the multivariate normal distribution and distribution of quadratic forms are included.

For this third edition, the material has been reorganised to develop the linear algebra in the first six chapters, to serve as a first course on linear algebra that is especially suitable for students of statistics or for those looking for a matrix theoretic approach to the subject. Other key features include:

coverage of topics such as rank additivity, inequalities for eigenvalues and singular values;

a new chapter on linear mixed models;

over seventy additional problems on rank: the matrix rank is an important and rich topic with connections to many aspects of linear algebra such as generalized inverses, idempotent matrices and partitioned matrices.

This text is aimed primarily at advanced undergraduate and first-year graduate students taking courses in linear algebra, linear models, multivariate analysis and design of experiments. A wealth of exercises, complete with hints and solutions, help to consolidate understanding. Researchers in mathematics and statistics will also find the book a useful source of results and problems.

Dettagli dell'edizione

• Editore: Springer
• Data di pubblicazione: 2012
• Lingua: Inglese
• ISBN 10: 1447127382
• ISBN 13: 9781447127383
• Rilegatura: Copertina flessibile
• Numero edizione: 3
• Numero di pagine: 176
• Contatto del produttore: ProductSafety@springernature.com; ProductSafety@springernature.com; ; Poststr. 9; Darmstadt; 64293; Germania