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Author:
Publisher:
ISBN:
Category : Legal briefs
Languages : en
Pages : 40
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Book Description
Author:
Publisher:
ISBN:
Category : Legal briefs
Languages : en
Pages : 40
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Book Description
Author:
Publisher:
ISBN:
Category : Legal briefs
Languages : en
Pages : 110
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Book Description
Author: Illinois. Appellate Court
Publisher:
ISBN:
Category : Law reports, digests, etc
Languages : en
Pages : 1222
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Book Description
Author: Illinois. Supreme Court
Publisher:
ISBN:
Category : Law reports, digests, etc
Languages : en
Pages : 396
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Book Description
Author: Clark Asahel Nichols
Publisher:
ISBN:
Category : Civil procedure
Languages : en
Pages : 774
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Author:
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ISBN:
Category : Illinois
Languages : en
Pages : 524
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Book Description
Author:
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ISBN:
Category : Law
Languages : en
Pages : 858
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Book Description
A complete restatement of the entire American law as developed by all reported cases.
Author: Illinois. Supreme Court
Publisher:
ISBN:
Category : Court calendars
Languages : en
Pages : 448
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Book Description
Author: Wendy L. Martinez
Publisher: CRC Press
ISBN: 1420010867
Category : Mathematics
Languages : en
Pages : 794
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Book Description
As with the bestselling first edition, Computational Statistics Handbook with MATLAB, Second Edition covers some of the most commonly used contemporary techniques in computational statistics. With a strong, practical focus on implementing the methods, the authors include algorithmic descriptions of the procedures as well as
Author: Thomas W. Yee
Publisher: Springer
ISBN: 149392818X
Category : Mathematics
Languages : en
Pages : 606
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Book Description
This book presents a greatly enlarged statistical framework compared to generalized linear models (GLMs) with which to approach regression modelling. Comprising of about half-a-dozen major classes of statistical models, and fortified with necessary infrastructure to make the models more fully operable, the framework allows analyses based on many semi-traditional applied statistics models to be performed as a coherent whole. Since their advent in 1972, GLMs have unified important distributions under a single umbrella with enormous implications. However, GLMs are not flexible enough to cope with the demands of practical data analysis. And data-driven GLMs, in the form of generalized additive models (GAMs), are also largely confined to the exponential family. The methodology here and accompanying software (the extensive VGAM R package) are directed at these limitations and are described comprehensively for the first time in one volume. This book treats distributions and classical models as generalized regression models, and the result is a much broader application base for GLMs and GAMs. The book can be used in senior undergraduate or first-year postgraduate courses on GLMs or categorical data analysis and as a methodology resource for VGAM users. In the second part of the book, the R package VGAM allows readers to grasp immediately applications of the methodology. R code is integrated in the text, and datasets are used throughout. Potential applications include ecology, finance, biostatistics, and social sciences. The methodological contribution of this book stands alone and does not require use of the VGAM package.
