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A User S Guide To Principal Components


A User S Guide To Principal Components
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A User S Guide To Principal Components


A User S Guide To Principal Components
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Author : J. Edward Jackson
language : en
Publisher: John Wiley & Sons
Release Date : 2005-01-21

A User S Guide To Principal Components written by J. Edward Jackson and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2005-01-21 with Mathematics categories.


WILEY-INTERSCIENCE PAPERBACK SERIES The Wiley-Interscience Paperback Series 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. From the Reviews of A User’s Guide to Principal Components "The book is aptly and correctly named–A User’s Guide. It is the kind of book that a user at any level, novice or skilled practitioner, would want to have at hand for autotutorial, for refresher, or as a general-purpose guide through the maze of modern PCA." –Technometrics "I recommend A User’s Guide to Principal Components to anyone who is running multivariate analyses, or who contemplates performing such analyses. Those who write their own software will find the book helpful in designing better programs. Those who use off-the-shelf software will find it invaluable in interpreting the results." –Mathematical Geology



A User S Guide To Principal Components


A User S Guide To Principal Components
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Author :
language : en
Publisher:
Release Date : 2005

A User S Guide To Principal Components written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2005 with categories.


Don't get bogged down in theoretical matters and computational techniques. Focus instead on practical aspects of data reduction and interpretation. Dealing with the "how-to-do-it" as well as the '"why-it-works," this paperback edition of a Wiley bestseller is designed for practitioners of principal component analysis. Among the topics explored are extension to p variables, scaling input data, inferential procedures, operations with group data, and vector interpretation.



Principal Components Analysis


Principal Components Analysis
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Author : George H. Dunteman
language : en
Publisher: SAGE
Release Date : 1989-05

Principal Components Analysis written by George H. Dunteman and has been published by SAGE this book supported file pdf, txt, epub, kindle and other format this book has been release on 1989-05 with Mathematics categories.


For anyone in need of a concise, introductory guide to principal components analysis, this book is a must. Through an effective use of simple mathematical-geometrical and multiple real-life examples (such as crime statistics, indicators of drug abuse, and educational expenditures) -- and by minimizing the use of matrix algebra -- the reader can quickly master and put this technique to immediate use.



Handbook Of Inter Rater Reliability 4th Edition


Handbook Of Inter Rater Reliability 4th Edition
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Author : Kilem L. Gwet
language : en
Publisher: Advanced Analytics, LLC
Release Date : 2014-09-07

Handbook Of Inter Rater Reliability 4th Edition written by Kilem L. Gwet and has been published by Advanced Analytics, LLC this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-09-07 with Medical categories.


The third edition of this book was very well received by researchers working in many different fields of research. The use of that text also gave these researchers the opportunity to raise questions, and express additional needs for materials on techniques poorly covered in the literature. For example, when designing an inter-rater reliability study, many researchers wanted to know how to determine the optimal number of raters and the optimal number of subjects that should participate in the experiment. Also, very little space in the literature has been devoted to the notion of intra-rater reliability, particularly for quantitative measurements. The fourth edition of this text addresses those needs, in addition to further refining the presentation of the material already covered in the third edition. Features of the Fourth Edition include: New material on sample size calculations for chance-corrected agreement coefficients, as well as for intraclass correlation coefficients. The researcher will be able to determine the optimal number raters, subjects, and trials per subject.The chapter entitled “Benchmarking Inter-Rater Reliability Coefficients” has been entirely rewritten.The introductory chapter has been substantially expanded to explore possible definitions of the notion of inter-rater reliability.All chapters have been revised to a large extent to improve their readability.



User S Guide To Principal Components


User S Guide To Principal Components
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Author : J. Edward Jackson
language : en
Publisher:
Release Date : 19??

User S Guide To Principal Components written by J. Edward Jackson and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 19?? with categories.




Practical Guide To Principal Component Methods In R


Practical Guide To Principal Component Methods In R
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Author : Alboukadel KASSAMBARA
language : en
Publisher: STHDA
Release Date : 2017-08-23

Practical Guide To Principal Component Methods In R written by Alboukadel KASSAMBARA and has been published by STHDA this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-08-23 with Education categories.


Although there are several good books on principal component methods (PCMs) and related topics, we felt that many of them are either too theoretical or too advanced. This book provides a solid practical guidance to summarize, visualize and interpret the most important information in a large multivariate data sets, using principal component methods in R. The visualization is based on the factoextra R package that we developed for creating easily beautiful ggplot2-based graphs from the output of PCMs. This book contains 4 parts. Part I provides a quick introduction to R and presents the key features of FactoMineR and factoextra. Part II describes classical principal component methods to analyze data sets containing, predominantly, either continuous or categorical variables. These methods include: Principal Component Analysis (PCA, for continuous variables), simple correspondence analysis (CA, for large contingency tables formed by two categorical variables) and Multiple CA (MCA, for a data set with more than 2 categorical variables). In Part III, you'll learn advanced methods for analyzing a data set containing a mix of variables (continuous and categorical) structured or not into groups: Factor Analysis of Mixed Data (FAMD) and Multiple Factor Analysis (MFA). Part IV covers hierarchical clustering on principal components (HCPC), which is useful for performing clustering with a data set containing only categorical variables or with a mixed data of categorical and continuous variables.



Principal Component Analysis


Principal Component Analysis
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Author : I.T. Jolliffe
language : en
Publisher: Springer Science & Business Media
Release Date : 2013-03-09

Principal Component Analysis written by I.T. Jolliffe 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 2013-03-09 with Mathematics categories.


Principal component analysis is probably the oldest and best known of the It was first introduced by Pearson (1901), techniques ofmultivariate analysis. and developed independently by Hotelling (1933). Like many multivariate methods, it was not widely used until the advent of electronic computers, but it is now weIl entrenched in virtually every statistical computer package. The central idea of principal component analysis is to reduce the dimen sionality of a data set in which there are a large number of interrelated variables, while retaining as much as possible of the variation present in the data set. This reduction is achieved by transforming to a new set of variables, the principal components, which are uncorrelated, and which are ordered so that the first few retain most of the variation present in all of the original variables. Computation of the principal components reduces to the solution of an eigenvalue-eigenvector problem for a positive-semidefinite symmetrie matrix. Thus, the definition and computation of principal components are straightforward but, as will be seen, this apparently simple technique has a wide variety of different applications, as weIl as a number of different deri vations. Any feelings that principal component analysis is a narrow subject should soon be dispelled by the present book; indeed some quite broad topics which are related to principal component analysis receive no more than a brief mention in the final two chapters.



Python Data Science Handbook


Python Data Science Handbook
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Author : Jake VanderPlas
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2016-11-21

Python Data Science Handbook written by Jake VanderPlas and has been published by "O'Reilly Media, Inc." this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-11-21 with Computers categories.


For many researchers, Python is a first-class tool mainly because of its libraries for storing, manipulating, and gaining insight from data. Several resources exist for individual pieces of this data science stack, but only with the Python Data Science Handbook do you get them all—IPython, NumPy, Pandas, Matplotlib, Scikit-Learn, and other related tools. Working scientists and data crunchers familiar with reading and writing Python code will find this comprehensive desk reference ideal for tackling day-to-day issues: manipulating, transforming, and cleaning data; visualizing different types of data; and using data to build statistical or machine learning models. Quite simply, this is the must-have reference for scientific computing in Python. With this handbook, you’ll learn how to use: IPython and Jupyter: provide computational environments for data scientists using Python NumPy: includes the ndarray for efficient storage and manipulation of dense data arrays in Python Pandas: features the DataFrame for efficient storage and manipulation of labeled/columnar data in Python Matplotlib: includes capabilities for a flexible range of data visualizations in Python Scikit-Learn: for efficient and clean Python implementations of the most important and established machine learning algorithms



Encyclopedia Of Spectroscopy And Spectrometry


Encyclopedia Of Spectroscopy And Spectrometry
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Author :
language : en
Publisher: Academic Press
Release Date : 2016-09-22

Encyclopedia Of Spectroscopy And Spectrometry written by and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-09-22 with Science categories.


This third edition of the Encyclopedia of Spectroscopy and Spectrometry, Three Volume Set provides authoritative and comprehensive coverage of all aspects of spectroscopy and closely related subjects that use the same fundamental principles, including mass spectrometry, imaging techniques and applications. It includes the history, theoretical background, details of instrumentation and technology, and current applications of the key areas of spectroscopy. The new edition will include over 80 new articles across the field. These will complement those from the previous edition, which have been brought up-to-date to reflect the latest trends in the field. Coverage in the third edition includes: Atomic spectroscopy Electronic spectroscopy Fundamentals in spectroscopy High-Energy spectroscopy Magnetic resonance Mass spectrometry Spatially-resolved spectroscopic analysis Vibrational, rotational and Raman spectroscopies The new edition is aimed at professional scientists seeking to familiarize themselves with particular topics quickly and easily. This major reference work continues to be clear and accessible and focus on the fundamental principles, techniques and applications of spectroscopy and spectrometry. Incorporates more than 150 color figures, 5,000 references, and 300 articles for a thorough examination of the field Highlights new research and promotes innovation in applied areas ranging from food science and forensics to biomedicine and health Presents a one-stop resource for quick access to answers and an in-depth examination of topics in the spectroscopy and spectrometry arenas



Multivariate Analysis In The Pharmaceutical Industry


Multivariate Analysis In The Pharmaceutical Industry
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Author : Ana Patricia Ferreira
language : en
Publisher: Academic Press
Release Date : 2018-04-24

Multivariate Analysis In The Pharmaceutical Industry written by Ana Patricia Ferreira and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-04-24 with Medical categories.


Multivariate Analysis in the Pharmaceutical Industry provides industry practitioners with guidance on multivariate data methods and their applications over the lifecycle of a pharmaceutical product, from process development, to routine manufacturing, focusing on the challenges specific to each step. It includes an overview of regulatory guidance specific to the use of these methods, along with perspectives on the applications of these methods that allow for testing, monitoring and controlling products and processes. The book seeks to put multivariate analysis into a pharmaceutical context for the benefit of pharmaceutical practitioners, potential practitioners, managers and regulators. Users will find a resources that addresses an unmet need on how pharmaceutical industry professionals can extract value from data that is routinely collected on products and processes, especially as these techniques become more widely used, and ultimately, expected by regulators. - Targets pharmaceutical industry practitioners and regulatory staff by addressing industry specific challenges - Includes case studies from different pharmaceutical companies and across product lifecycle of to introduce readers to the breadth of applications - Contains information on the current regulatory framework which will shape how multivariate analysis (MVA) is used in years to come