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Probability & Statistics - Multivariate Analysis

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Applied Univariate, Bivariate, and Multivariate Statistics Using Python
by Denis, Danile J.       
(Hardcover - English - 9781119578147)
Applied Univariate, Bivariate, and Multivariate Statistics Using Python A practical, "how-to" reference for anyone performing essential statistical analyses and data management tasks in Python Applied Univariate, Bivariate, and Multivariate Statistics Using Python delivers a comprehensive introduction to a wide range of statistical methods performed using Python in a single, one-stop reference. The book contains user-friendly guidance and instructions on using Python to run a variety of statistical procedures without getting bogged down in unnecessary theory. Throughout, the author emphasizes a set of computational tools used in the discovery of empirical patt ..
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Multivariate Dependencies: Models, Analysis and Interpretation
by Cox, D. R.    Wermuth, Nanny   
(Paperback - English - 9780367401375)
Large observational studies involving research questions that require the measurement of several features on each individual arise in many fields including the social and medical sciences. This book sets out both the general concepts and the more technical statistical issues involved in analysis and interpretation. Numerous illustrative examples are described in outline and four studies are discussed in some detail. The use of graphical representations of dependencies and independencies among the features under study is stressed, both to incorporate available knowledge at the planning stage of an analysis and to summarize aspects important for interpretation af ..
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The Geometry of Multivariate Statistics
by Wickens, Thomas D.       
(Hardcover - English - 9780805816563)
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 ap ..
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Advances in Latent Class Analysis: A Festschrift in Honor of C. Mitchell Dayton
by Hancock, Gregory R.    Harring, Jeffrey R.    Macready, George B.
(Paperback - English - 9781641135610)
What is latent class analysis? If you asked that question thirty or forty years ago you would have gotten a different answer than you would today. Closer to its time of inception, latent class analysis was viewed primarily as a categorical data analysis technique, often framed as a factor analysis model where both the measured variable indicators and underlying latent variables are categorical. Today, however, it rests within much broader mixture and diagnostic modeling framework, integrating measured and latent variables that may be categorical and or continuous, and where latent classes serve to define the subpopulations for whom many aspects of the focal meas ..
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Statistics for Spatial Data
by Cressie, Noel       
(Paperback - English - 9781119114611)
The Wiley Classics Library consists of selected books that have been made more accessible to consumers in an effort to increase global appeal and general circulation. With these new unabridged softcover volumes, Wiley hopes to extend the lives of these works by making them available to future generations of statisticians, mathematicians, and scientists. Spatial statistics -- analyzing spatial data through statistical models -- has proven exceptionally versatile, encompassing problems ranging from the microscopic to the astronomic. However, for the scientist and engineer faced only with scattered and uneven treatments of the subject in the scientific literature ..
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A Step-by-Step Guide to Exploratory Factor Analysis with Stata
by Watkins, Marley W.       
(Paperback - English - 9780367710323)
This is a concise, easy to use, step-by-step guide for applied researchers conducting exploratory factor analysis (EFA) using Stata . In this book, Dr. Watkins systematically reviews each decision step in EFA with screen shots of Stata code and recommends evidence-based best practice procedures. This is an eminently applied, practical approach with few or no formulas and is aimed at readers with little to no mathematical background. Dr. Watkins maintains an accessible tone throughout and uses minimal jargon and formula to help facilitate grasp of the key issues users will face when applying EFA, along with how to implement, interpret, and report results. Copio ..
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Statistical Analysis of Spatial and Spatio-Temporal Point Patterns
by Diggle, Peter J.       
(Paperback - English - 9781032477473)
Written by a prominent statistician and author, the first edition of this bestseller broke new ground in the then emerging subject of spatial statistics with its coverage of spatial point patterns. Retaining all the material from the second edition and adding substantial new material, strong Statistical Analysis of Spatial and Spatio-Temporal Point Patterns, Third Edition strong presents models and statistical methods for analyzing spatially referenced point process data. Reflected in the title, this third edition now covers spatio-temporal point patterns. It explores the methodological developments from the last decade along with diverse applications that u ..
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Analysis of Incomplete Multivariate Data
by Schafer, J. L.       
(Paperback - English - 9781032477992)
The last two decades have seen enormous developments in statistical methods for incomplete data. Thealgorithm 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. Analysis of Incomplete Multivariate Data helps bridge the gap between theory and practice, making these missing-data tools accessible to a broad audience. It presents a unified, Bayesian approach to the analysis of incomplete multiva ..
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A Step-by-Step Guide to Exploratory Factor Analysis with Stata
by Watkins, Marley W.       
(Hardcover - English - 9780367710996)
This is a concise, easy to use, step-by-step guide for applied researchers conducting exploratory factor analysis (EFA) using Stata . In this book, Dr. Watkins systematically reviews each decision step in EFA with screen shots of Stata code and recommends evidence-based best practice procedures. This is an eminently applied, practical approach with few or no formulas and is aimed at readers with little to no mathematical background. Dr. Watkins maintains an accessible tone throughout and uses minimal jargon and formula to help facilitate grasp of the key issues users will face when applying EFA, along with how to implement, interpret, and report results. Copi ..
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Practical Multivariate Analysis
by Afifi, Abdelmonem    May, Susanne    Donatello, Robin
(Paperback - English - 9781032088471)
This is the sixth edition of a popular textbook on multivariate analysis. Well-regarded for its practical and accessible approach, with excellent examples and good guidance on computing, the book is particularly popular for teaching outside statistics, i.e. in epidemiology, social science, business, etc. The sixth edition has been updated with a new chapter on data visualization, a distinction made between exploratory and confirmatory analyses and a new section on generalized estimating equations and many new updates throughout. This new edition will enable the book to continue as one of the leading textbooks in the area, particularly for non-statisticians. br ..
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Analysis of Integrated Data
by Zhang, Li-Chun    Chambers, Raymond L.   
(Paperback - English - 9781032092782)
The advent of "Big Data" has brought with it a rapid diversification of data sources, requiring analysis that accounts for the fact that these data have often been generated and recorded for different reasons. Data integration involves combining data residing in different sources to enable statistical inference, or to generate new statistical data for purposes that cannot be served by each source on its own. This can yield significant gains for scientific as well as commercial investigations. br br br br However, valid analysis of such data should allow for the additional uncertainty due to entity ambiguity, whenever it is not possible to state with ce ..
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Handbook of Multiple Comparisons
by Cui, Xinping    Dickhaus, Thorsten    Ding, Ying
(Hardcover - English - 9780367140670)
Written by experts that include originators of some key ideas, chapters in the Handbook of Multiple Testing cover multiple comparison problems big and small, with guidance toward error rate control and insights on how principles developed earlier can be applied to current and emerging problems. Some highlights of the coverages are as follows. Error rate control is useful for controlling the incorrect decision rate. Chapter 1 introduces Tukey's original multiple comparison error rates and point to how they have been applied and adapted to modern multiple comparison problems as discussed in the later chapters. Principles endure. While the closed testing principl ..
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Functional and Shape Data Analysis
by Srivastava, Anuj    Klassen, Eric P.   
(Hardcover - English - 9781493940189)
This textbook for courses on function data analysis and shape data analysis describes how to define, compare, and mathematically represent shapes, with a focus on statistical modeling and inference. It is aimed at graduate students in analysis in statistics, engineering, applied mathematics, neuroscience, biology, bioinformatics, and other related areas. The interdisciplinary nature of the broad range of ideas covered--from introductory theory to algorithmic implementations and some statistical case studies--is meant to familiarize graduate students with an array of tools that are relevant in developing computational solutions for shape and related analyses. The ..
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Multilevel Modeling Using Mplus
by Finch, Holmes    Bolin, Jocelyn   
(Paperback - English - 9781498748247)
This book is designed primarily for upper level undergraduate and graduate level students taking a course in multilevel modelling and or statistical modelling with a large multilevel modelling component. The focus is on presenting the theory and practice of major multilevel modelling techniques in a variety of contexts, using Mplus as the software tool, and demonstrating the various functions available for these analyses in Mplus, which is widely used by researchers in various fields, including most of the social sciences. In particular, Mplus offers users a wide array of tools for latent variable modelling, including for multilevel data. ..
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GeoStatistics by Example: Hands on approach using R
by Anderson, Faye       
(Paperback - English - 9781535278225)
This is an applied handbook on geostatistics with annotated examples using S-Plus or R. This is the first book ever explaining geostatistics by example, applied for everyone who could use it from the many disciplines of geology, statistics, medical geography, environmental research, any other field that has data with locations. Although the examples are presented in R, their results and interpretations are applicable to any other software attempting geostatistical analyses. ..
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Simulating Copulas: Stochastic Models, Sampling Algorithms, and Applications (Second Edition)
by Mai, Jan-Frederik    Scherer, Matthias   
(Hardcover - English - 9789813149243)
'The book remains a valuable tool both for statisticians who are already familiar with the theory of copulas and just need to develop sampling algorithms, and for practitioners who want to learn copulas and implement the simulation techniques needed to exploit the potential of copulas in applications.'Mathematical ReviewsThe book provides the background on simulating copulas and multivariate distributions in general. It unifies the scattered literature on the simulation of various families of copulas (elliptical, Archimedean, Marshall-Olkin type, etc.) as well as on different construction principles (factor models, pair-copula construction, etc.). The book is se ..
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Numerical Methods for Structured Markov Chains
by Bini, Dario A.    Latouche, Guy    Meini, Beatrice
(Hardcover - English - 9780198527688)
Intersecting two large research areas--numerical analysis and applied probability quering theory--this book is a self -contained introduction to the numerical solution of structured Markov chains, which have a wide applicability in queueing theory and stochastic modeling. Aimed at graduates and researchers in numerical analysis, applied mathematics, probability, engineering and computer science it provides a thorough overview of the current literature. The book, consisting of nine chapters, is presented in three parts. Part 1 covers a basic description of the fundamental concepts related to Markov chains, a systematic treatment of the structure matrix tools, inc ..
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Basic Statistics in Multivariate Analysis
by Randolph, Karen A.    Myers, Laura L.   
(Paperback - English - 9780199764044)
The complexity of social problems necessitates that social work researchers understand and apply multivariate statistical methods in their investigations. In this pocket guide, the authors introduce readers to three of the more frequently used multivariate methods in social work research with an emphasis on basic statistics. The primary aim is to prepare entry-level doctoral students and early career social work researchers in the use of multivariate methods by providing an easy-to-understand presentation, building on the basic statistics that inform them. The pocket guide begins with a review of basic statistics, hypothesis testing with inferential statistics, ..
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Analysis of Longitudinal Data second edition
by Diggle, Peter    Heagerty, Patrick    Liang, Kung-Yee
(Hardcover - English - 9780198524847)
The new edition of this important text has been completely revised and expanded to become the most up-to-date and thorough professional reference text in this fast-moving and important area of biostatistics. Two new chapters have been added on fully parametric models for discrete repeated measures data and on statistical models for time-dependent predictors where there may be feedback between the predictor and response variables. It also contains the many useful features of the previous edition such as, design issues, exploratory methods of analysis, linear models for continuous data, and models and methods for handling data and missing values. br ..
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Principles of Multivariate Analysis: A User's Perspective
by Krzanowski, W. J.       
(Paperback - English - 9780198507086)
This book is an introduction to the principles and methodology of modern multivariate statistical analysis. It's emphasis is problem-oriented and stresses geometrical intuition in preference to algebraic manipulation. Mathematical sections that are not essential for practical understanding of the techniques are clearly indicated so that they may be skipped if necessary. Discrete and mixed variable techniques are presented as well as continuous variable techniques. New additions to this update include references, a survey of the most recent developments and a new appendix which traces developments that have taken place in the years since publication of the first ..
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