Some Optimal Properties of Ranking Procedures with Applications in Multivariate Analysis PDF Download

Author: Morris L. Eaton
Publisher:
ISBN:
Category :
Languages : en
Pages : 198

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Author: Edward J. Dudewicz
Publisher:
ISBN:
Category : Mathematics
Languages : en
Pages : 652

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Author: Leon J. Gleser
Publisher: Springer Science & Business Media
ISBN: 1461236789
Category : Mathematics
Languages : en
Pages : 512

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Book Description
Published in honor of the sixty-fifth birthday of Professor Ingram Olkin of Stanford University. Part I contains a brief biography of Professor Olkin and an interview with him discussing his career and his research interests. Part II contains 32 technical papers written in Professor Olkin's honor by his collaborators, colleagues, and Ph.D. students. These original papers cover a wealth of topics in mathematical and applied statistics, including probability inequalities and characterizations, multivariate analysis and association, linear and nonlinear models, ranking and selection, experimental design, and approaches to statistical inference. The volume reflects the wide range of Professor Olkin's interests in and contributions to research in statistics, and provides an overview of new developments in these areas of research.

Author:
Publisher:
ISBN:
Category : Mathematical statistics
Languages : en
Pages : 1182

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Author: Shanti S. Gupta
Publisher: SIAM
ISBN: 0898715326
Category : Mathematics
Languages : en
Pages : 592

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An encyclopaedic coverage of the literature in the area of ranking and selection procedures. It also deals with the estimation of unknown ordered parameters. This book can serve as a text for a graduate topics course in ranking and selection. It is also a valuable reference for researchers and practitioners.

Author: Institute of Mathematical Statistics
Publisher:
ISBN:
Category : Mathematical statistics
Languages : en
Pages : 646

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Author:
Publisher:
ISBN:
Category : Dissertations, Academic
Languages : en
Pages : 946

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Author:
Publisher:
ISBN:
Category : Weights and measures
Languages : en
Pages : 574

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Author: Brian Everitt
Publisher: Springer Science & Business Media
ISBN: 1441996508
Category : Mathematics
Languages : en
Pages : 284

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Book Description
The majority of data sets collected by researchers in all disciplines are multivariate, meaning that several measurements, observations, or recordings are taken on each of the units in the data set. These units might be human subjects, archaeological artifacts, countries, or a vast variety of other things. In a few cases, it may be sensible to isolate each variable and study it separately, but in most instances all the variables need to be examined simultaneously in order to fully grasp the structure and key features of the data. For this purpose, one or another method of multivariate analysis might be helpful, and it is with such methods that this book is largely concerned. Multivariate analysis includes methods both for describing and exploring such data and for making formal inferences about them. The aim of all the techniques is, in general sense, to display or extract the signal in the data in the presence of noise and to find out what the data show us in the midst of their apparent chaos. An Introduction to Applied Multivariate Analysis with R explores the correct application of these methods so as to extract as much information as possible from the data at hand, particularly as some type of graphical representation, via the R software. Throughout the book, the authors give many examples of R code used to apply the multivariate techniques to multivariate data.

Author:
Publisher:
ISBN:
Category : Dissertations, Academic
Languages : en
Pages : 858

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