Описание: Uses the method of maximum likelihood to a large extent to ensure reasonable, and in some cases optimal procedures. This work treats the basic and important topics in multivariate statistics.
Описание: An accessible guide to the multivariate time series tools used in numerous real-world applications Multivariate Time Series Analysis: With R and Financial Applications is the much anticipated sequel coming from one of the most influential and prominent experts on the topic of time series.
Описание: Suitable for those who needs to communicate complex research results, this title includes four new chapters that cover writing about interactions, writing about event history analysis, writing about multilevel models, and the "Goldilocks principle" for choosing the right size contrast for interpreting results for different variables.
Описание: 'Big data' poses challenges that require both classical multivariate methods and contemporary techniques from machine learning and engineering. This modern text equips you for the new world - integrating the old and the new, fusing theory and practice and bridging the gap to statistical learning. The theoretical framework includes formal statements that set out clearly the guaranteed 'safe operating zone' for the methods and allow you to assess whether data is in the zone, or near enough. Extensive examples showcase the strengths and limitations of different methods with small classical data, data from medicine, biology, marketing and finance, high-dimensional data from bioinformatics, functional data from proteomics, and simulated data. High-dimension low-sample-size data gets special attention. Several data sets are revisited repeatedly to allow comparison of methods. Generous use of colour, algorithms, Matlab code, and problem sets complete the package. Suitable for master's/graduate students in statistics and researchers in data-rich disciplines.
Описание: Methods of multivariate analysis and the use of a suitable software package such as S-PLUS or RT are required to examine the multivariate data sets collected by researchers. This book covers the multivariate methodology along with some basic theory for each method described. It also gives the necessary R and S-PLUS code for each analysis.
Автор: Wackernagel Название: Multivariate Geostatistics ISBN: 3540441425 ISBN-13(EAN): 9783540441427 Издательство: Springer Рейтинг: Цена: 10449 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book presents an introduction to geostatistics stressing the multivariate aspects for scientists, engineers or statisticians. Geostatistics offers a variety of models, methods and techniques for the analysis, estimation and display of multivariate data distributed in space or time. This book presents a brief review of statistical concepts, a detailed introduction to linear geostatistics and an account of three basic methods of multivariate analysis. The third edition of this very successful textbook contains an advanced presentation of linear models for multivariate spatial or temporal data, of nonlinear models and methods for selection problems with change of suppport as well as an introduction to non-stationary geostatistics with special focus on the external drift method. Applications from very different areas of science, as well as exercises with solutions, are provided to help convey the general ideas.
Автор: Waller N & Meehl P Название: Multivariate Taxometric Procedures ISBN: 0761902570 ISBN-13(EAN): 9780761902577 Издательство: Sage Publications Рейтинг: Цена: 9893 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Can taxometric procedures be used to distinguish types (species, latent classes, taxa) from continua (dimensions, latent traits, factors); and, if so, how? Aimed at demystifying this process, Waller and Meehl unpack Meehl`s work on the MAXCOV-HITMAX procedure to reveal the underlying rationale of MAXCOV in simple terms and show how this technique can be profitably used in a variety of disciplines by researchers in their taxonomic work.
Описание: Multivariate methods are now widely used by scientists in quantitative sciences and statistics due to the ready availability of computer packages for performing the calculations. Access to suitable computer software is essential to using these methods, however a working knowledge of how multivariate statistical methods can be used is a prerequisite to the use of any brand of software. Multivariate Statistical Methods: A Primer introduces the methods to non-mathematicians and provides a general overview without overwhelming the novice with comprehensive details.This third edition is a thoroughly revised, updated edition of a best-selling introductory textbook and primer. It retains the author's trademark clear, concise style and focuses on examples in the biological and environmental sciences. Topics new to this edition include confirmatory factor analysis, the use of mixture models for cluster analysis, and the emerging techniques of data mining and neural networks. While not linked to any specific software package, the book now includes an appendix comparing and contrasting various statistical software packages, such as Stata, Statistica, SAS, and Genstat. The author also notes which software was used for a particar example, when appropriate.In his efforts to produce a book that is as short as possible and that enables you to begin to use multivariate methods in an intelligent manner, the author has produced a succinct and handy reference. With updated information on multivariate analyses, new examples using the latest software, and updated references, this book will bring you up to speed with useful tools for statistical analysis.
Автор: Robb J. Muirhead Название: Aspects of Multivariate Statistical Theory ISBN: 0471769851 ISBN-13(EAN): 9780471769859 Издательство: Wiley Рейтинг: Цена: 13398 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: "Aspects of Multivariate Statistical Theory" presents a classical mathematical treatment of the techniques, distributions, and inferences based on multivariate normal distribution. Noncentral distribution theory, decision theoretic estimation of the parameters of a multivariate normal distribution, and the uses of spherical and elliptical distributions in multivariate analysis are introduced. Advances in multivariate analysis are discussed, including decision theory and robustness. The book also includes tables of percentage points of many of the standard likelihood statistics used in multivariate statistical procedures. This definitive resource provides in-depth discussion of the multivariate field and serves admirably as both a textbook and reference.
Описание: A collection of eleven articles, which deal with special topics in Multivariate Approximation and Interpolation. The material discussed here has applications in many areas of Applied Mathematics, such as in Computer Aided Geometric Design, in Mathematical Modelling, in Signal and Image Processing and in Machine Learning, to mention a few.
Описание: Illustrates major concepts in matrix algebra, linear structures, and eigenstructures geometrically, numerically, and algebraically. This book emphasizes the applications of these techniques by discussing potential solutions to problems outlined. It also presents small numerical examples of the various concepts.
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