Permutation Complexity in Dynamical Systems, Jos? Amig?

Автор: Godfrey C. Onwubolu; Donald Davendra
Название: Differential Evolution: A Handbook for Global Permutation-Based Combinatorial Optimization
ISBN: 3662518929 ISBN-13(EAN): 9783662518922
Издательство: Springer
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Описание: This book, the first devoted entirely to the subject, presents in detail the various permutative-based combinatorial differential evolution formulations by their initiators in an easy-to-follow manner through numerous illustrations and computer code.

Автор: Paul W. Mielke; Kenneth J. Berry
Название: Permutation Methods
ISBN: 1441924167 ISBN-13(EAN): 9781441924162
Издательство: Springer
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Описание: This is the second edition of the comprehensive treatment of statistical inference using permutation techniques. This updated version places increased emphasis on the use of alternative permutation statistical tests based on metric Euclidean distance functions.

Автор: Pesarin
Название: Permutation Tests for Complex Data - Theory, Applications and Software
ISBN: 0470516410 ISBN-13(EAN): 9780470516416
Издательство: Wiley
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Цена: 113990.00 T
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Описание: Complex multivariate testing problems are frequently encountered in many scientific disciplines, such as engineering, medicine and the social sciences. As a result, modern statistics needs permutation testing for complex data with low sample size and many variables, especially in observational studies.

Автор: Kenneth J. Berry; Janis E. Johnston; Paul W. Mielk
Название: A Chronicle of Permutation Statistical Methods
ISBN: 3319027433 ISBN-13(EAN): 9783319027432
Издательство: Springer
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Цена: 102480.00 T
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Описание: This book covers the birth and historical development of permutation statistical methods from the early 1920s to the present day. Using an accessible, non-mathematical approach, the book presents permutation analogs of many well-known statistical tests.

Автор: Kenneth J. Berry; Paul W. Mielke Jr.; Janis E. Joh
Название: Permutation Statistical Methods
ISBN: 3319287680 ISBN-13(EAN): 9783319287683
Издательство: Springer
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Описание: Preface.- 1.Introduction.- 2.Completely Randomized Data.- 3.Randomized Designs: Interval Data.- 4.Regression Analysis of Interval Data.- 5.Randomized Designs: Ordinal Data, I.- 6.Randomized Designs: Ordinal Data, II.- 7.Randomized Designs: Nominal Data.- 8.Randomized Designs: Nominal Data.- 9.Randomized Block Designs: Interval Data.- 10.Randomized Block Designs: Ordinal Data.- 11.Randomized Block Designs: Nominal Data.- Epilogue.- References.- Author Index.- Subject Index.

Автор: W.C. Holland
Название: Ordered Groups and Infinite Permutation Groups
ISBN: 0792338537 ISBN-13(EAN): 9780792338536
Издательство: Springer
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Цена: 88500.00 T
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Описание: Represents the happy confluence of Ordered Groups and Infinite Permutation Groups. This book covers topics such as lattice-ordered groups, ordered permutation groups, Jordan groups, reconstruction problems, groups with few orbits, the separation theorem, and automorphisms of symmetric groups.

Автор: A. Kerber
Название: Representations of Permutation Groups I
ISBN: 3540056939 ISBN-13(EAN): 9783540056935
Издательство: Springer
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Цена: 23250.00 T
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Автор: J. Hinze
Название: The Permutation Group in Physics and Chemistry
ISBN: 3540097074 ISBN-13(EAN): 9783540097075
Издательство: Springer
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Цена: 83850.00 T
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Описание: The permutation group has gained prominence in the fundamental research in diverse areas of physics and chemistry.

Автор: Mark W. Short
Название: The Primitive Soluble Permutation Groups of Degree Less than 256
ISBN: 3540555013 ISBN-13(EAN): 9783540555018
Издательство: Springer
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Цена: 23280.00 T
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Описание: This monograph addresses the problem of describing all primitive soluble permutation groups of a given degree, with particular reference to those degrees less than 256. The theory is presented in detail and in a way that utilizes modern terminology.

Автор: Meenaxi Bhattacharjee; R?gnvaldur G. M?ller; Dugal
Название: Notes on Infinite Permutation Groups
ISBN: 3540649654 ISBN-13(EAN): 9783540649656
Издательство: Springer
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Описание: Based on a course of lectures by the authors at the Indian Institute of Technology, Guwahati, this work covers aspects of infinite permutation groups theory and some related model theoretic constructions. There is basic background in both group theory and the necessary model theory.

Автор: Gregory Butler
Название: Fundamental Algorithms for Permutation Groups
ISBN: 3540549552 ISBN-13(EAN): 9783540549550
Издательство: Springer
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Описание: This is the first-ever book on computational group theory. It covers the fundamental algorithms for permutation groups, with emphasis on the details of data structures and implementation which make the algorithms effective when applied to realistic problems.

Автор: Phillip I. Good
Название: Permutation, Parametric, and Bootstrap Tests of Hypotheses
ISBN: 1441919074 ISBN-13(EAN): 9781441919076
Издательство: Springer
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Цена: 153720.00 T
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Описание: This text is intended to provide a strong theoretical background in testing hypotheses and decision theory for those who will be practicing in the real worldorwhowillbeparticipatinginthetrainingofreal-worldstatisticiansand biostatisticians. In previous editions of this text, my rhetoric was somewhat tentative. I was saying, in e?ect, "Gee guys, permutation methods provide a practical real-world alternative to asymptotic parametric approximations. Why not give them a try?" But today, the theory, the software, and the hardware have come together. Distribution-free permutation procedures are the primary method for testing hypotheses. Parametric procedures and the bootstrap are to be reserved for the few situations in which they may be applicable. Four factors have forced this change: 1. Desire by workers in applied ?elds to use the most powerful statistic for their applications. Such workers may not be aware of the fundamental lemma of Neyman and Pearson, but they know that the statistic they wanttouse--acomplexscoreoraratioofscores, doesnothaveanalready well-tabulated distribution. 2. Pressure from regulatory agencies for the use of methods that yield exact signi?cance levels, not approximations. 3. A growing recognition that most real-world data are drawn from mixtures of populations. 4. A growing recognition that missing data is inevitable, balanced designs the exception. Thus, it seems natural that the theory of testing hypothesis and the more general decision theory in which it is embedded should be introduced via the permutation tests. On the other hand, certain relatively robust param- ric tests such as Student's t continue to play an essential role in statistical practice.