Statistical Factor Analysis and Related Methods (Hardcover)

Alexander T. Basilevsky

ISBN 10: 0471570826 / ISBN 13: 9780471570820

Editore: John Wiley & Sons Inc, New York, 1994

Riguardo questo articolo

Hardcover. Statistical Factor Analysis and Related Methods Theory andApplications In bridging the gap between the mathematical andstatistical theory of factor analysis, this new work represents thefirst unified treatment of the theory and practice of factoranalysis and latent variable models. It focuses on such areasas: * The classical principal components model and sample-populationinference * Several extensions and modifications of principal components,including Q and three-mode analysis and principal components in thecomplex domain * Maximum likelihood and weighted factor models, factoridentification, factor rotation, and the estimation of factorscores * The use of factor models in conjunction with various types ofdata including time series, spatial data, rank orders, and nominalvariable * Applications of factor models to the estimation of functionalforms and to least squares of regression estimators The purpose of this work is to provide a unified treatment of both the theory and practice of factor analysis and latent variables models. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.

Codice articolo 9780471570820

Dati bibliografici

• Titolo: Statistical Factor Analysis and Related Methods (Hardcover)
• Editore: John Wiley & Sons Inc, New York
• Data di pubblicazione: 1994
• Lingua: Inglese
• ISBN 10: 0471570826
• ISBN 13: 9780471570820
• Rilegatura: Hardcover
• Edizione: prima edizione
• Condizione: new

Descrizione articolo

Riassunto

Statistical Factor Analysis and Related Methods Theory andApplications In bridging the gap between the mathematical andstatistical theory of factor analysis, this new work represents thefirst unified treatment of the theory and practice of factoranalysis and latent variable models. It focuses on such areasas:
* The classical principal components model and sample-populationinference
* Several extensions and modifications of principal components,including Q and three-mode analysis and principal components in thecomplex domain
* Maximum likelihood and weighted factor models, factoridentification, factor rotation, and the estimation of factorscores
* The use of factor models in conjunction with various types ofdata including time series, spatial data, rank orders, and nominalvariable
* Applications of factor models to the estimation of functionalforms and to least squares of regression estimators

Informazioni sull?autore

About the author ALEXANDER BASILEVSKY is Professor of Mathematics and Statistics at the University of Winnipeg. He frequently serves as a professional consultant to both government and industry. In addition to numerous scholarly papers and government reports, Professor Basilevsky is the author of Applied Matrix Algebra in Statistical Sciences and coauthor of An Analysis of the U.S. Income Maintenance Experiments. He is a member of the Canadian Statistical Association, the American Statistical Association, and the Statistical Association of Manitoba, of which he is former president-at-large. Professor Basilevsky received his PhD in statistics/econometrics from the University of Southampton, England.