Exploratory Multivariate Analysis by Example Using R


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Applied Multivariate Statistical Analysis, Fourth Edition
26 May 2015

Applied Multivariate Statistical Analysis, Fourth Edition

Wolfgang Karl Hardle, "Applied Multivariate Statistical Analysis, Fourth Edition"
English | 2015 | ISBN-10: 3662451700 | 581 pages | pdf | 11 MB

Focusing on high-dimensional applications, this 4th edition presents the tools and concepts used in multivariate data analysis in a style that is also accessible for non-mathematicians and practitioners. It surveys the basic principles and emphasizes both exploratory and inferential statistics; a new chapter on Variable Selection (Lasso, SCAD and Elastic Net) has also been added.
Multivariate Analysis of Ecological Data using CANOCO
10 August 2013

Multivariate Analysis of Ecological Data using CANOCO
Jan Lep, Petr milauer, "Multivariate Analysis of Ecological Data using CANOCO"
English | ISBN: 0521891086 | 2003 | PDF | 283 pages | 3,2 mb


Multivariate statistical methods are described in this study and advice is given on how best to apply these methods using CANOCO software. Data sets and program files for the case studies are provided on a supporting website.

Methods of Multivariate Analysis
9 August 2013

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Methods of Multivariate Analysis
English | 2012 | ISBN: 0470178965 | 800 pages | PDF | 16 MB

Filled with new and timely content, Methods of Multivariate Analysis, Third Edition provides examples and exercises based on more than sixty real data sets from a wide variety of scientific fields. It takes a "methods" approach to the subject, placing an emphasis on how students and practitioners can employ multivariate analysis in real-life situations.
An Introduction to Multivariate Statistical Analysis by T. W. Anderson
20 May 2015

An Introduction to Multivariate Statistical Analysis by T. W. Anderson

An Introduction to Multivariate Statistical Analysis by T. W. Anderson
English | July 25, 2003 | ISBN: 0471360910 | 739 Pages | PDF | 12 MB

Perfected over three editions and more than forty years, this field- and classroom-tested reference:
* Uses the method of maximum likelihood to a large extent to ensure reasonable, and in some cases optimal procedures.
Applied Multivariate Data Analysis, 2nd Edition
15 July 2014

Applied Multivariate Data Analysis, 2nd Edition
Brian S. Everitt, Graham Dunn, "Applied Multivariate Data Analysis, 2nd Edition"
English | ISBN: 0470711175 | 2001 | 354 pages | PDF | 41 MB
Aspects Of Multivariate Statistical Analysis In Geology - E.Savazzi
25 August 2010

Aspects Of Multivariate Statistical Analysis In Geology - E.Savazzi

Aspects Of Multivariate Statistical Analysis In Geology - E.Savazzi
Publisher: Elsevier Science | English | PDF | ISBN-10: 0444504125 | 250 pages | 11.1MB

The book presents multivariate statistical methods useful in geological analysis. The essential distinction between multivariate analysis as applied to full-space data (measurements on lengths, heights, breadths etc.) and compositional data is emphasized with particular reference to geochemical data. Each of the methods is accompanied by a practically oriented computer program and backed up by appropriate examples. The computer programs are provided on a compact disk together with trial data-sets and examples of the output.
Applied Multivariate Statistical Analysis
22 September 2013

Applied Multivariate Statistical Analysis
Applied Multivariate Statistical Analysis
English | 2012 | ISBN: 3642172288 | 533 pages | PDF | 6.4 MB
Analysis of Incomplete Multivariate Data
5 July 2013

Analysis of Incomplete Multivariate Data

Analysis of Incomplete Multivariate Data
English | 444 pages | ISBN-10: 0412040611 | PDF | 6.77 MB

The last two decades have seen enormous developments in statistical methods for incomplete data. The EM algorithm and its extensions, multiple imputation, and Markov Chain Monte Carlo provide a set of flexible and reliable tools from inference in large classes of missing-data problems. Yet, in practical terms, those developments have had surprisingly little impact on the way most data analysts handle missing values on a routine basis.
Exploratory Data Analysis Using Fisher Information
27 December 2010

Exploratory Data Analysis Using Fisher Information

Roy Frieden, Robert A. Gatenby, "Exploratory Data Analysis Using Fisher Information"
Springer | 2006 | ISBN: 1846285062 | 363 pages | PDF | 13,6 MB

The basic goal of a research scientist is to understand a given, unknown system. This innovative book develops a systematic approach for achieving this goal. All science is ultimately dependent upon observation which, in turn, requires a flow of information. Fisher information, in particular, is found to provide the key to understanding the system. It is developed as a new tool of exploratory data analysis, and is applied to a wide scope of systems problems. These range from molecules in a gas to biological organisms in their ecologies, to the socio-economic organization of people in their societies, to the physical constants in the universe and, ultimately, to proto-universes in the multiverse.
Multivariate Polysplines: Applications to Numerical and Wavelet Analysis
1 April 2011

Multivariate Polysplines: Applications to Numerical and Wavelet Analysis

Multivariate Polysplines: Applications to Numerical and Wavelet Analysis

2001 | 498 | ISBN: 0124224903 | DJVU | 5 Mb

Multivariate polysplines are a new mathematical technique that has arisen from a synthesis of approximation theory and the theory of partial differential equations. It is an invaluable means to interpolate practical data with smooth functions.Multivariate polysplines have applications in the design of surfaces and "smoothing" that are essential in computer aided geometric design (CAGD and CAD/CAM systems), geophysics, magnetism, geodesy, geography, wavelet analysis and signal and image processing. In many cases involving practical data in these areas, polysplines are proving more effective than well-established methods, such as kKriging, radial basis functions, thin plate splines and minimum curvature. ...