Автор: Barbara Tabachnick Название: Using Multivariate Statistics: International Edition ISBN: 0205465250 ISBN-13(EAN): 9780205465255 Издательство: Pearson Education Цена: 3717 р. Наличие на складе: Невозможна поставка. Описание: Provides advanced students with a comprehensive introduction to commonly encountered statistical and multivariate techniques, while assuming only a limited knowledge of higher level mathematics. Each technique chapter: discusses tests for assumptions of analysis, presents a small example and describes varieties of analysis.
Автор: Tabachnick Barbara Название: Using Multivariate Statistics ISBN: 0205890814 ISBN-13(EAN): 9780205890811 Издательство: Pearson Education Цена: 34360 р. Наличие на складе: Поставка под заказ.
Автор: Tabachnick Barbara Название: Using Multivariate Statistics ISBN: 0205849571 ISBN-13(EAN): 9780205849574 Издательство: Pearson Education Цена: 34500 р. Наличие на складе: Поставка под заказ. Описание: "A Practical Approach to using Multivariate Analyses" "Using Multivariate Statistics," 6th edition provides advanced undergraduate as well as graduate students with a timely and comprehensive introduction to today's most commonly encountered statistical and multivariate techniques, while assuming only a limited knowledge of higher-level mathematics. This text's practical approach focuses on the benefits and limitations of applications of a technique to a data set -- when, why, and how to do it. Learning GoalsUpon completing this book, readers should be able to:
Learn to conduct numerous types of multivariate statistical analyses
Find the best technique to use
Understand Limitations to applications
Learn how to use SPSS and SAS syntax and output
Note: MySearchLab with eText does not come automatically packaged with this text. To purchase MySearchLab with eText, please visit www.mysearchlab.com or you can purchase a ValuePack of the text + MySearchLab with eText (at no additional cost). ValuePack ISBN-10: 0205885667 / ValuePack ISBN-13: 9780205885664
Название: Using Multivariate Statistics ISBN: 0673994147 ISBN-13(EAN): 9780673994141 Издательство: Pearson Education Цена: 9395 р. Наличие на складе: Поставка под заказ.
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.
Автор: Koch Название: Analysis of Multivariate and High-Dimensional Data ISBN: 0521887933 ISBN-13(EAN): 9780521887939 Издательство: Cambridge Academ Рейтинг: Цена: 5932 р. Наличие на складе: Есть у поставщика Поставка под заказ.
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: 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.
Автор: Crowder Название: Multivariate Survival Analysis and Competing Risks ISBN: 1439875219 ISBN-13(EAN): 9781439875216 Издательство: Taylor&Francis Рейтинг: Цена: 12018 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Multivariate Survival Analysis and Competing Risks introduces univariate survival analysis and extends it to the multivariate case. It covers competing risks and counting processes and provides many real-world examples, exercises, and R code. The text discusses survival data, survival distributions, frailty models, parametric methods, multivariate data and distributions, copulas, continuous failure, parametric likelihood inference, and non- and semi-parametric methods. There are many books covering survival analysis, but very few that cover the multivariate case in any depth. Written for a graduate-level audience in statistics/biostatistics, this book includes practical exercises and R code for the examples. The author is renowned for his clear writing style, and this book continues that trend. It is an excellent reference for graduate students and researchers looking for grounding in this burgeoning field of research.
Автор: Flury Название: A First Course in Multivariate Statistics ISBN: 038798206X ISBN-13(EAN): 9780387982069 Издательство: Springer Рейтинг: Цена: 8971 р. Наличие на складе: Поставка под заказ.
Описание: This is author-approved bcc: multivariate statistical methods have evolved from the pioneering work of Fisher, Pearson, Hotelling, and others, motivated by
practical problems in biological and other sciences. In the past fifty years the field has grown rapidly, largely due to the availability of computers that make the calculations feasible. This
book gives a comprehensive and self-contained introduction, carefully balancing mathematical theory and practical applications.
"A First Course in Multivariate Statistics"
starts at an elementary level, developing concepts of multivariate distributions from first principles. There is a chapter on the multivariate normal distribution that reviews the classical
parametric theory. Methods of estimation are explored using the plug-in principles as well as maximum likelihood.
Two chapters on discrimination and classification, including
logistic regression, are at the core of the book. Methods of testing hypotheses are developed from heuristic principles, followed by likelihood ratio tests and permutation tests. The
powerful self-consistency principle is used to introduce principal components as a method of approximation.
The book concludes with a chapter on finite mixture analysis, a
topic of great practical and theoretical importance. Unique features of "A First Course in Multivariate Statistics" include the presentation of the EM algorithm for maximum likelihood
estimation with incomplete data, resampling based methods of testing, a brief in
roduction to the theory of elliptical distributions, and a comparison of linear and quadratic classification rules. Examples from biology, anthropology, chemistry, and other area are worked
out.
Автор: Crowder Название: Multivariate Survival Analysis and Competing Risks ISBN: 1138199605 ISBN-13(EAN): 9781138199606 Издательство: Taylor&Francis Рейтинг: Цена: 4492 р. Наличие на складе: Поставка под заказ.
Описание: Multivariate Survival Analysis and Competing Risks introduces univariate survival analysis and extends it to the multivariate case. It covers competing risks and counting processes and provides many real-world examples, exercises, and R code. The text discusses survival data, survival distributions, frailty models, parametric methods, multivariate data and distributions, copulas, continuous failure, parametric likelihood inference, and non- and semi-parametric methods. There are many books covering survival analysis, but very few that cover the multivariate case in any depth. Written for a graduate-level audience in statistics/biostatistics, this book includes practical exercises and R code for the examples. The author is renowned for his clear writing style, and this book continues that trend. It is an excellent reference for graduate students and researchers looking for grounding in this burgeoning field of research.
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.
Full of real-world case studies and practical advice, Exploratory Multivariate Analysis by Example Using R, Second Edition focuses on four fundamental methods of multivariate exploratory data analysis that are most suitable for applications. It covers principal component analysis (PCA) when variables are quantitative, correspondence analysis (CA) and multiple correspondence analysis (MCA) when variables are categorical, and hierarchical cluster analysis.
The authors take a geometric point of view that provides a unified vision for exploring multivariate data tables. Within this framework, they present the principles, indicators, and ways of representing and visualising objects that are common to the exploratory methods. The authors show how to use categorical variables in a PCA context in which variables are quantitative, how to handle more than two categorical variables in a CA context in which there are originally two variables, and how to add quantitative variables in an MCA context in which variables are categorical. They also illustrate the methods using examples from various fields, with related R code accessible in the FactoMineR package developed by the authors.
The book has been written using minimal mathematics so as to appeal to applied statisticians, as well as researchers from various disciplines, including medical research and the social sciences. Readers can use the theory, examples, and software presented in this book in order to be fully equipped to tackle real-life multivariate data.
Описание: This handbook explains the appropriate uses of multivariate procedures and mathematical modelling techniques, and prescribes practices that should enable applied researchers to use these procedures effectively without needing to concern themselves with the mathematical basis.
Автор: Wickens Название: The Geometry of Multivariate Statistics ISBN: 1138882828 ISBN-13(EAN): 9781138882829 Издательство: Taylor&Francis Рейтинг: Цена: 4597 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: A traditional approach to developing multivariate statistical theory is algebraic. Sets of observations are represented by matrices, linear combinations are formed from these matrices by multiplying them by coefficient matrices, and useful statistics are found by imposing various criteria of optimization on these combinations. Matrix algebra is the vehicle for these calculations. A second approach is computational. Since many users find that they do not need to know the mathematical basis of the techniques as long as they have a way to transform data into results, the computation can be done by a package of computer programs that somebody else has written. An approach from this perspective emphasizes how the computer packages are used, and is usually coupled with rules that allow one to extract the most important numbers from the output and interpret them. Useful as both approaches are--particularly when combined--they can overlook an important aspect of multivariate analysis. To apply it correctly, one needs a way to conceptualize the multivariate relationships that exist among variables. This book is designed to help the reader develop a way of thinking about multivariate statistics, as well as to understand in a broader and more intuitive sense what the procedures do and how their results are interpreted. Presenting important procedures of multivariate statistical theory geometrically, the author hopes that this emphasis on the geometry will give the reader a coherent picture into which all the multivariate techniques fit.
Автор: Harris Название: A Primer of Multivariate Statistics ISBN: 0415645581 ISBN-13(EAN): 9780415645584 Издательство: Taylor&Francis Цена: 4597 р. Наличие на складе: Невозможна поставка.
Описание: Drawing upon more than 30 years of experience in working with statistics, Dr. Richard J. Harris has updated A Primer of Multivariate Statistics to provide a model of balance between how-to and why. This classic text covers multivariate techniques with a taste of latent variable approaches. Throughout the book there is a focus on the importance of describing and testing one's interpretations of the emergent variables that are produced by multivariate analysis. This edition retains its conversational writing style while focusing on classical techniques. The book gives the reader a feel for why one should consider diving into more detailed treatments of computer-modeling and latent-variable techniques, such as non-recursive path analysis, confirmatory factor analysis, and hierarchical linear modeling. Throughout the book there is a focus on the importance of describing and testing one's interpretations of the emergent variables that are produced by multivariate analysis.
Автор: Kollo Tonu, Rosen D. von Название: Advanced Multivariate Statistics with Matrices ISBN: 1402034180 ISBN-13(EAN): 9781402034183 Издательство: Springer Рейтинг: Цена: 11219 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book presents the authors' personal selection of topics in multivariate statistical analysis with emphasis on tools and techniques. Topics included range from definitions of multivariate moments, multivariate distributions, asymptotic distributions of commonly used statistics and density approximations to a modern treatment of multivariate linear models. The theory used is based on matrix algebra and linear spaces and applies lattice theory in a systematic way. Many of the results are obtained by utilizing matrix derivatives which in turn are built up from the Kronecker product and vec-operator. The matrix normal, Wishart and elliptical distributions are studied in detail. In particular, several moment relations are given. Together with the derivatives of density functions, formulae are presented for density approximations, generalizing classical Edgeworth expansions. The asymptotic distributions of many commonly used statistics are also derived. In the final part of the book the Growth Curve model and its various extensions are studied.The book will be of particular interest to researchers but could also be appropriate as a text-book for graduate courses on multivariate analysis or matrix algebra.
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