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An Introduction To Applied Multivariate Analysis With R


An Introduction To Applied Multivariate Analysis With R
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An Introduction To Applied Multivariate Analysis With R


An Introduction To Applied Multivariate Analysis With R
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Author : Brian Everitt
language : en
Publisher: Springer Science & Business Media
Release Date : 2011-04-23

An Introduction To Applied Multivariate Analysis With R written by Brian Everitt and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-04-23 with Mathematics categories.


The majority of data sets collected by researchers in all disciplines are multivariate, meaning that several measurements, observations, or recordings are taken on each of the units in the data set. These units might be human subjects, archaeological artifacts, countries, or a vast variety of other things. In a few cases, it may be sensible to isolate each variable and study it separately, but in most instances all the variables need to be examined simultaneously in order to fully grasp the structure and key features of the data. For this purpose, one or another method of multivariate analysis might be helpful, and it is with such methods that this book is largely concerned. Multivariate analysis includes methods both for describing and exploring such data and for making formal inferences about them. The aim of all the techniques is, in general sense, to display or extract the signal in the data in the presence of noise and to find out what the data show us in the midst of their apparent chaos. An Introduction to Applied Multivariate Analysis with R explores the correct application of these methods so as to extract as much information as possible from the data at hand, particularly as some type of graphical representation, via the R software. Throughout the book, the authors give many examples of R code used to apply the multivariate techniques to multivariate data.



An Introduction To Applied Multivariate Analysis


An Introduction To Applied Multivariate Analysis
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Author : Tenko Raykov
language : en
Publisher: Routledge
Release Date : 2008-03-10

An Introduction To Applied Multivariate Analysis written by Tenko Raykov and has been published by Routledge this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008-03-10 with Business & Economics categories.


This comprehensive text introduces readers to the most commonly used multivariate techniques at an introductory, non-technical level. By focusing on the fundamentals, readers are better prepared for more advanced applied pursuits, particularly on topics that are most critical to the behavioral, social, and educational sciences. Analogies betwe



Applied Multivariate Statistics With R


Applied Multivariate Statistics With R
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Author : Daniel Zelterman
language : en
Publisher: Springer Nature
Release Date : 2023-01-20

Applied Multivariate Statistics With R written by Daniel Zelterman and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-01-20 with Medical categories.


Now in its second edition, this book brings multivariate statistics to graduate-level practitioners, making these analytical methods accessible without lengthy mathematical derivations. Using the open source shareware program R, Dr. Zelterman demonstrates the process and outcomes for a wide array of multivariate statistical applications. Chapters cover graphical displays; linear algebra; univariate, bivariate and multivariate normal distributions; factor methods; linear regression; discrimination and classification; clustering; time series models; and additional methods. He uses practical examples from diverse disciplines, to welcome readers from a variety of academic specialties. Each chapter includes exercises, real data sets, and R implementations. The book avoids theoretical derivations beyond those needed to fully appreciate the methods. Prior experience with R is not necessary. New to this edition are chapters devoted to longitudinal studies and the clustering of large data. It is an excellent resource for students of multivariate statistics, as well as practitioners in the health and life sciences who are looking to integrate statistics into their work.



Using R With Multivariate Statistics


Using R With Multivariate Statistics
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Author : Randall E. Schumacker
language : en
Publisher: SAGE Publications
Release Date : 2015-06-18

Using R With Multivariate Statistics written by Randall E. Schumacker and has been published by SAGE Publications this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-06-18 with Social Science categories.


Using R with Multivariate Statistics by Randall E. Schumacker is a quick guide to using R, free-access software available for Windows and Mac operating systems that allows users to customize statistical analysis. Designed to serve as a companion to a more comprehensive text on multivariate statistics, this book helps students and researchers in the social and behavioral sciences get up to speed with using R. It provides data analysis examples, R code, computer output, and explanation of results for every multivariate statistical application included. In addition, R code for some of the data set examples used in more comprehensive texts is included, so students can run examples in R and compare results to those obtained using SAS, SPSS, or STATA. A unique feature of the book is the photographs and biographies of famous persons in the field of multivariate statistics.



R For Medicine And Biology


R For Medicine And Biology
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Author : Paul D. Lewis
language : en
Publisher: Jones & Bartlett Learning
Release Date : 2009-05-08

R For Medicine And Biology written by Paul D. Lewis and has been published by Jones & Bartlett Learning this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009-05-08 with Science categories.


R is quickly becoming the number one choice for users in the fields of biology, medicine, and bioinformatics as their main means of storing, processing, sharing, and analyzing biomedical data. R for Medicine and Biology is a step-by-step guide through the use of the statistical environment R, as used in a biomedical domain. Ideal for healthcare professionals, scientists, informaticists, and statistical experts, this resource will provide even the novice programmer with the tools necessary to process and analyze their data using the R environment. Introductory chapters guide readers in how to obtain, install, and become familiar with R and provide a clear introduction to the programming language using numerous worked examples. Later chapters outline how R can be used, not just for biomedical data analysis, but also as an environment for the processing, storing, reporting, and sharing of data and results. The remainder of the book explores areas of R application to common domains of biomedical informatics, including imaging, statistical analysis, data mining/modeling, pathology informatics, epidemiology, clinical trials, and metadata usage. R for Medicine and Biology will provide you with a single desk reference for the R environment and its many capabilities.



Basic Elements Of Computational Statistics


Basic Elements Of Computational Statistics
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Author : Wolfgang Karl Härdle
language : en
Publisher: Springer
Release Date : 2017-09-29

Basic Elements Of Computational Statistics written by Wolfgang Karl Härdle and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-09-29 with Computers categories.


This textbook on computational statistics presents tools and concepts of univariate and multivariate statistical data analysis with a strong focus on applications and implementations in the statistical software R. It covers mathematical, statistical as well as programming problems in computational statistics and contains a wide variety of practical examples. In addition to the numerous R sniplets presented in the text, all computer programs (quantlets) and data sets to the book are available on GitHub and referred to in the book. This enables the reader to fully reproduce as well as modify and adjust all examples to their needs. The book is intended for advanced undergraduate and first-year graduate students as well as for data analysts new to the job who would like a tour of the various statistical tools in a data analysis workshop. The experienced reader with a good knowledge of statistics and programming might skip some sections on univariate models and enjoy the various ma thematical roots of multivariate techniques. The Quantlet platform quantlet.de, quantlet.com, quantlet.org is an integrated QuantNet environment consisting of different types of statistics-related documents and program codes. Its goal is to promote reproducibility and offer a platform for sharing validated knowledge native to the social web. QuantNet and the corresponding Data-Driven Documents-based visualization allows readers to reproduce the tables, pictures and calculations inside this Springer book.



Fibre Reinforced Concrete Improvements And Innovations


Fibre Reinforced Concrete Improvements And Innovations
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Author : Pedro Serna
language : en
Publisher: Springer Nature
Release Date : 2020-11-05

Fibre Reinforced Concrete Improvements And Innovations written by Pedro Serna and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-11-05 with Technology & Engineering categories.


This volume highlights the latest advances, innovations, and applications in the field of fibre reinforced concrete (FRC) and discusses a diverse range of topics concerning FRC: rheology and early-age properties, mechanical properties, codes and standards, long-term properties, durability, analytical and numerical models, quality control, structural and Industrial applications, smart FRC’s, nanotechnologies related to FRC, textile reinforced concrete, structural design and UHPFRC. The contributions present improved traditional and new ideas that will open novel research directions and foster multidisciplinary collaboration between different specialists. Although the symposium was postponed, the book gathers peer-reviewed papers selected in 2020 for the RILEM-fib International Symposium on Fibre Reinforced Concrete (BEFIB).



Learn R


Learn R
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Author : Pedro J. Aphalo
language : en
Publisher: CRC Press
Release Date : 2024-04-26

Learn R written by Pedro J. Aphalo and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-04-26 with Computers categories.


Learning a computer language like R can be either frustrating, fun or boring. Having fun requires challenges that wake up the learner’s curiosity but also provide an emotional reward for overcoming them. The book is designed so that it includes smaller and bigger challenges, in what I call playgrounds, in the hope that all readers will enjoy their path to R fluency. Fluency in the use of a language is a skill that is acquired through practice and exploration. For students and professionals in the biological sciences, humanities and many applied fields, recognizing the parallels between R and natural languages should help them feel at home with R. The approach I use is similar to that of a travel guide, encouraging exploration and describing the available alternatives and how to reach them. The intention is to guide the reader through the R landscape of 2024 and beyond. What is new in the second edition? Text expanded by more than 25% to include additional R features and gentler and more detailed explanations Contains 24 new diagrams and flowcharts, seven new tables, and revised text and code examples for clarity All three indexes were expanded, and answers to 28 frequently asked questions added What will you find in this book? Programming concepts explained as they apply to current R Emphasis on the role of abstractions in programming Few prescriptive rules—mostly the author’s preferences together with alternatives Presentation of the R language emphasizing the “R way of doing things” Tutoring for “programming in the small” using scripts for data analysis Explanation of the differences between R proper and extensions for data wrangling The grammar of graphics is described as a language for the construction of data visualisations Examples of data exchange between R and the foreign world using common file formats Coaching to become an independent R user, capable of writing original scripts and solving future challenges



Intelligent Computing And Optimization


Intelligent Computing And Optimization
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Author : Pandian Vasant
language : en
Publisher: Springer Nature
Release Date : 2023-12-19

Intelligent Computing And Optimization written by Pandian Vasant and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-12-19 with Computers categories.


This book of Springer Nature is another proof of Springer’s outstanding greatness on the lively interface of Holistic Computational Optimization, Green IoTs, Smart Modeling, and Deep Learning! It is a masterpiece of what our community of academics and experts can provide when an interconnected approach of joint, mutual, and meta-learning is supported by advanced operational research and experience of the World-Leader Springer Nature! The 6th edition of International Conference on Intelligent Computing and Optimization took place at G Hua Hin Resort & Mall on April 27–28, 2023, with tremendous support from the global research scholars across the planet. Objective is to celebrate “Research Novelty with Compassion and Wisdom” with researchers, scholars, experts, and investigators in Intelligent Computing and Optimization across the globe, to share knowledge, experience, and innovation—a marvelous opportunity for discourse and mutuality by novel research, invention, and creativity. This proceedings book of the 6th ICO’2023 is published by Springer Nature—Quality Label of Enlightenment.



Structural Equation Modelling With Partial Least Squares Using Stata And R


Structural Equation Modelling With Partial Least Squares Using Stata And R
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Author : Mehmet Mehmetoglu
language : en
Publisher: CRC Press
Release Date : 2020-12-22

Structural Equation Modelling With Partial Least Squares Using Stata And R written by Mehmet Mehmetoglu and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-12-22 with Mathematics categories.


Partial least squares structural equation modelling (PLS-SEM) is becoming a popular statistical framework in many fields and disciplines of the social sciences. The main reason for this popularity is that PLS-SEM can be used to estimate models including latent variables, observed variables, or a combination of these. The popularity of PLS-SEM is predicted to increase even more as a result of the development of new and more robust estimation approaches, such as consistent PLS-SEM. The traditional and modern estimation methods for PLS-SEM are now readily facilitated by both open-source and commercial software packages. This book presents PLS-SEM as a useful practical statistical toolbox that can be used for estimating many different types of research models. In so doing, the authors provide the necessary technical prerequisites and theoretical treatment of various aspects of PLS-SEM prior to practical applications. What makes the book unique is the fact that it thoroughly explains and extensively uses comprehensive Stata (plssem) and R (cSEM and plspm) packages for carrying out PLS-SEM analysis. The book aims to help the reader understand the mechanics behind PLS-SEM as well as performing it for publication purposes. Features: Intuitive and technical explanations of PLS-SEM methods Complete explanations of Stata and R packages Lots of example applications of the methodology Detailed interpretation of software output Reporting of a PLS-SEM study Github repository for supplementary book material The book is primarily aimed at researchers and graduate students from statistics, social science, psychology, and other disciplines. Technical details have been moved from the main body of the text into appendices, but it would be useful if the reader has a solid background in linear regression analysis.