The R Software

Author: Pierre Lafaye de Micheaux
Publisher: Springer Science & Business
ISBN: 1461490200
Format: PDF, Kindle
Download Now
The contents of The R Software are presented so as to be both comprehensive and easy for the reader to use. Besides its application as a self-learning text, this book can support lectures on R at any level from beginner to advanced. This book can serve as a textbook on R for beginners as well as more advanced users, working on Windows, MacOs or Linux OSes. The first part of the book deals with the heart of the R language and its fundamental concepts, including data organization, import and export, various manipulations, documentation, plots, programming and maintenance. The last chapter in this part deals with oriented object programming as well as interfacing R with C/C++ or Fortran, and contains a section on debugging techniques. This is followed by the second part of the book, which provides detailed explanations on how to perform many standard statistical analyses, mainly in the Biostatistics field. Topics from mathematical and statistical settings that are included are matrix operations, integration, optimization, descriptive statistics, simulations, confidence intervals and hypothesis testing, simple and multiple linear regression, and analysis of variance. Each statistical chapter in the second part relies on one or more real biomedical data sets, kindly made available by the Bordeaux School of Public Health (Institut de Santé Publique, d'Épidémiologie et de Développement - ISPED) and described at the beginning of the book. Each chapter ends with an assessment section: memorandum of most important terms, followed by a section of theoretical exercises (to be done on paper), which can be used as questions for a test. Moreover, worksheets enable the reader to check his new abilities in R. Solutions to all exercises and worksheets are included in this book.

Machine Learning An overview with the help of R software

Author: Editor IJSMI
Publisher: IJSMI
ISBN: 1790122627
Format: PDF, ePub, Mobi
Download Now
This book intends to provide an overview of Machine Learning and its algorithms & models with help of R software. Machine learning forms the basis for Artificial Intelligence which will play a crucial role in day to day life of human beings in the near future. A basic understanding of machine learning is required, as its application is widely seen in different fields such as banks and financial sectors, manufacturing, aviation, transportation and medical field. The book covers machine learning classification algorithms such as K-Nearest Neighborhood, Naïve Bayes, Decision Trees and also Artificial Neural Networks and Support Vector Machines. It is recommended to refer author’s book on Application of Statistical Tools in Biomedical Domain: An Overview with Help of Software (https://www.amazon.com/dp/1986988554) and Essentials of Bio-Statistics: An overview with the help of Software https://www.amazon.com/dp/B07GRBXX7D if you need to familiarize yourself with the basic statistical knowledge. Editor International Journal of Statistics and Medical Informatics www.ijsmi.com/book.php Amazon link https://www.amazon.com/dp/1790122627 (Paper Back) https://www.amazon.com/dp/B07KQSN447 (Kindle Edition)

Software Development for SAP R 3

Author: Ulrich Mende
Publisher: Springer Science & Business Media
ISBN: 3642572251
Format: PDF, Mobi
Download Now
The ABAP/4 workbench presented here is built on the enterprise-wide data model of R/3 and contains all the tools needed for the effective development of large program systems in distributed teams. The book explains how to apply the development environment such that R/3 users and advisors can extend and adapt the system to their special needs. In particular, the text focuses on how to solve interface problems and the integration of desktop PCs into R/3. The source code for all examples is included on the accompanying diskette.

Statistics for Censored Environmental Data Using Minitab and R

Author: Dennis R. Helsel
Publisher: John Wiley & Sons
ISBN: 1118162765
Format: PDF, Mobi
Download Now
Praise for the First Edition " . . . an excellent addition to an upper-level undergraduatecourse on environmental statistics, and . . . a 'must-have' deskreference for environmental practitioners dealing with censoreddatasets." —Vadose Zone Journal Statistical Methods for Censored Environmental Data UsingMinitab® and R, Second Edition introduces and explains methodsfor analyzing and interpreting censored data in the environmentalsciences. Adapting survival analysis techniques from other fields,the book translates well-established methods from other disciplinesinto new solutions for environmental studies. This new edition applies methods of survival analysis, includingmethods for interval-censored data to the interpretation oflow-level contaminants in environmental sciences and occupationalhealth. Now incorporating the freely available R software as wellas Minitab® into the discussed analyses, the book featuresnewly developed and updated material including: A new chapter on multivariate methods for censored data Use of interval-censored methods for treating true nondetects aslower than and separate from values between the detection andquantitation limits ("remarked data") A section on summing data with nondetects A newly written introduction that discusses invasive data,showing why substitution methods fail Expanded coverage of graphical methods for censored data The author writes in a style that focuses on applications ratherthan derivations, with chapters organized by key objectives such ascomputing intervals, comparing groups, and correlation. Examplesaccompany each procedure, utilizing real-world data that can beanalyzed using the Minitab® and R software macros available onthe book's related website, and extensive references direct readersto authoritative literature from the environmental sciences. Statistics for Censored Environmental Data Using Minitab®and R, Second Edition is an excellent book for courses onenvironmental statistics at the upper-undergraduate and graduatelevels. The book also serves as a valuable referencefor¿environmental professionals, biologists, and ecologistswho focus on the water sciences, air quality, and soil science.

SAS and R

Author: Ken Kleinman
Publisher: CRC Press
ISBN: 1420070592
Format: PDF, ePub
Download Now
An All-in-One Resource for Using SAS and R to Carry out Common Tasks Provides a path between languages that is easier than reading complete documentation SAS and R: Data Management, Statistical Analysis, and Graphics presents an easy way to learn how to perform an analytical task in both SAS and R, without having to navigate through the extensive, idiosyncratic, and sometimes unwieldy software documentation. The book covers many common tasks, such as data management, descriptive summaries, inferential procedures, regression analysis, and the creation of graphics, along with more complex applications. Takes an innovative, easy-to-understand, dictionary-like approach Through the extensive indexing, cross-referencing, and worked examples in this text, users can directly find and implement the material they need. The book enables easier mobility between the two systems: SAS users can look up tasks in the SAS index and then find the associated R code while R users can benefit from the R index in a similar manner. Demonstrating the code in action and facilitating exploration, the authors present extensive example analyses that employ a single data set from the HELP study. They offer the data sets and code for download on the book’s website.

Software for Data Analysis

Author: John Chambers
Publisher: Springer Science & Business Media
ISBN: 9780387759364
Format: PDF, ePub
Download Now
John Chambers turns his attention to R, the enormously successful open-source system based on the S language. His book guides the reader through programming with R, beginning with simple interactive use and progressing by gradual stages, starting with simple functions. More advanced programming techniques can be added as needed, allowing users to grow into software contributors, benefiting their careers and the community. R packages provide a powerful mechanism for contributions to be organized and communicated. This is the only advanced programming book on R, written by the author of the S language from which R evolved.

Wavelet Methods in Statistics with R

Author: Guy Nason
Publisher: Springer Science & Business Media
ISBN: 0387759611
Format: PDF, Mobi
Download Now
This book contains information on how to tackle many important problems using a multiscale statistical approach. It focuses on how to use multiscale methods and discusses methodological and applied considerations.

Time Series Analysis

Author: Jonathan D. Cryer
Publisher: Springer Science & Business Media
ISBN: 038775959X
Format: PDF, ePub, Mobi
Download Now
This book has been developed for a one-semester course usually attended by students in statistics, economics, business, engineering, and quantitative social sciences. A unique feature of this edition is its integration with the R computing environment. Basic applied statistics is assumed through multiple regression. Calculus is assumed only to the extent of minimizing sums of squares but a calculus-based introduction to statistics is necessary for a thorough understanding of some of the theory. Actual time series data drawn from various disciplines are used throughout the book to illustrate the methodology.

Arbeitsbuch der Angewandten Statistik

Author: Philipp Otto
Publisher: Springer-Verlag
ISBN: 3662492121
Format: PDF, Kindle
Download Now
Das Arbeitsbuch stellt eine Aufgabensammlung mit detaillierten Lösungen zur Einführung in die Angewandte Statistik für Studenten zur Verfügung. Die Aufgaben umfassen dabei die Themengebiete, welche in etwa in drei Semestern Statistikausbildung gelehrt werden. Damit ist das Arbeitsbuch insbesondere für Studierende der Wirtschaftswissenschaften, Humanmedizin, Psychologie, Ingenieurswissenschaften sowie Informatik von Interesse. Insgesamt wird durch interessante, teilweise reale und teilweise fiktive Sachverhalte das Lernen des ansonsten eher trockenen vermittelten Stoffes erleichtert. Praktische Aufgaben, die mithilfe der Statistiksoftware R gelöst werden müssen, sind besonders gekennzeichnet. Am Ende des Buches gibt es Aufgaben zu gemischten Themengebieten zur Klausurvorbereitung.