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Classical statistical analysis depends on many assumptions about the nature of data and the population from which the samples were drawn. Permutation tests depend only on the data gathered and, although computationally intensive, provide powerful alternatives to conventional analysis techniques. Most commonly-used parametric and permutation statistical tests, such as the matched-pairs t test and analysis of variance, are based on non-metric squared distance functions that have very poor robustness characteristics. This Second Edition places increased emphasis on the use of alternative…mehr

Produktbeschreibung
Classical statistical analysis depends on many assumptions about the nature of data and the population from which the samples were drawn. Permutation tests depend only on the data gathered and, although computationally intensive, provide powerful alternatives to conventional analysis techniques. Most commonly-used parametric and permutation statistical tests, such as the matched-pairs t test and analysis of variance, are based on non-metric squared distance functions that have very poor robustness characteristics. This Second Edition places increased emphasis on the use of alternative permutation statistical tests based on metric Euclidean distance functions that have excellent robustness characteristics. These alternative permutation techniques provide many powerful multivariate tests including multivariate multiple regression analyses.


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Autorenporträt
Paul W. Mielke Jr., Colorado State University, Fort Collins, CO, USA / Kenneth J. Berry, Colorado State University, Fort Collins, CO, USA
Rezensionen
From the Reviews: "[T]his is a nicely written book that contains many important and useful topics, and I am certan that many pracitioners and researchers will find the new edition beneficial." (Technometrics, May 2008, Vol. 50 No. 2) "This is a very well-written text that extensively covers permutation-based tests in a general framework. It has been revised and extended by nearly 100 pages since the 2001 edition. …This book is packed with real-data examples and dozens of simulation studies exploring the properties of permutation-based tests and contrasting them with their typical parametric 'competitors.' The authors do not shy away from presenting the mathematical underpinnings of the methods, and do so in a very transparent and easy-to-follow manner so there is sufficient detail to implement the methods in your favorite software … . That is not a concern if you are familiar with FORTRAN-77, as the authors have provided over 100 FORTRAN programs an associated datasets for download in Unix-compatible and Windows-compatible format. These well-commented programs are briefly described in Appendix A with subsections organized by chapter. …Permutation Methods is a superb book that is highly recommended." ( Journal of the American Statistical Association, Dec. 2009, Vol. 104, No. 488)