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Up-to-Date Guidance from One of the Foremost Members of the R Core Team Written by John M. Chambers, the leading developer of the original S software, Extending R covers key concepts and techniques in R to support analysis and research projects. It presents the core ideas of R, provides programming guidance for projects of all scales, and introduces new, valuable techniques that extend R. The book first describes the fundamental characteristics and background of R, giving readers a foundation for the remainder of the text. It next discusses topics relevant to programming with R, including the apparatus that supports extensions. The book then extends R’s data structures through object-oriented programming, which is the key technique for coping with complexity. The book also incorporates a new structure for interfaces applicable to a variety of languages. A reflection of what R is today, this guide explains how to design and organize extensions to R by correctly using objects, functions, and interfaces. It enables current and future users to add their own contributions and packages to R. A 2017 Choice Outstanding Academic Title
Up-to-Date Guidance from One of the Foremost Members of the R Core Team Written by John M. Chambers, the leading developer of the original S software, Extending R covers key concepts and techniques in R to support analysis and research projects. It presents the core ideas of R, provides programming guidance for projects of all scales, and introduces new, valuable techniques that extend R. The book first describes the fundamental characteristics and background of R, giving readers a foundation for the remainder of the text. It next discusses topics relevant to programming with R, including the apparatus that supports extensions. The book then extends R’s data structures through object-oriented programming, which is the key technique for coping with complexity. The book also incorporates a new structure for interfaces applicable to a variety of languages. A reflection of what R is today, this guide explains how to design and organize extensions to R by correctly using objects, functions, and interfaces. It enables current and future users to add their own contributions and packages to R. A 2017 Choice Outstanding Academic Title
A Hands-On Way to Learning Data AnalysisPart of the core of statistics, linear models are used to make predictions and explain the relationship between the response and the predictors. Understanding linear models is crucial to a broader competence in the practice of statistics. Linear Models with R, Second Edition explains how to use linear models
Module Theory, Extending Modules and Generalizations by Adnan Tercan,Canan C. Yücel Pdf
The main focus of this monograph is to offer a comprehensive presentation of known and new results on various generalizations of CS-modules and CS-rings. Extending (or CS) modules are generalizations of injective (and also semisimple or uniform) modules. While the theory of CS-modules is well documented in monographs and textbooks, results on generalized forms of the CS property as well as dual notions are far less present in the literature. With their work the authors provide a solid background to module theory, accessible to anyone familiar with basic abstract algebra. The focus of the book is on direct sums of CS-modules and classes of modules related to CS-modules, such as relative (injective) ejective modules, (quasi) continuous modules, and lifting modules. In particular, matrix CS-rings are studied and clear proofs of fundamental decomposition results on CS-modules over commutative domains are given, thus complementing existing monographs in this area. Open problems round out the work and establish the basis for further developments in the field. The main text is complemented by a wealth of examples and exercises.
Module theory is an important tool for many different branches of mathematics, as well as being an interesting subject in its own right. Within module theory, the concept of injective modules is particularly important. Extending modules form a natural class of modules which is more general than the class of injective modules but retains many of its
Extending Power BI with Python and R by Luca Zavarella,Francesca Lazzeri Pdf
Perform more advanced analysis and manipulation of your data beyond what Power BI can do to unlock valuable insights using Python and R Key FeaturesGet the most out of Python and R with Power BI by implementing non-trivial codeLeverage the toolset of Python and R chunks to inject scripts into your Power BI dashboardsImplement new techniques for ingesting, enriching, and visualizing data with Python and R in Power BIBook Description Python and R allow you to extend Power BI capabilities to simplify ingestion and transformation activities, enhance dashboards, and highlight insights. With this book, you'll be able to make your artifacts far more interesting and rich in insights using analytical languages. You'll start by learning how to configure your Power BI environment to use your Python and R scripts. The book then explores data ingestion and data transformation extensions, and advances to focus on data augmentation and data visualization. You'll understand how to import data from external sources and transform them using complex algorithms. The book helps you implement personal data de-identification methods such as pseudonymization, anonymization, and masking in Power BI. You'll be able to call external APIs to enrich your data much more quickly using Python programming and R programming. Later, you'll learn advanced Python and R techniques to perform in-depth analysis and extract valuable information using statistics and machine learning. You'll also understand the main statistical features of datasets by plotting multiple visual graphs in the process of creating a machine learning model. By the end of this book, you'll be able to enrich your Power BI data models and visualizations using complex algorithms in Python and R. What you will learnDiscover best practices for using Python and R in Power BI productsUse Python and R to perform complex data manipulations in Power BIApply data anonymization and data pseudonymization in Power BILog data and load large datasets in Power BI using Python and REnrich your Power BI dashboards using external APIs and machine learning modelsExtract insights from your data using linear optimization and other algorithmsHandle outliers and missing values for multivariate and time-series dataCreate any visualization, as complex as you want, using R scriptsWho this book is for This book is for business analysts, business intelligence professionals, and data scientists who already use Microsoft Power BI and want to add more value to their analysis using Python and R. Working knowledge of Power BI is required to make the most of this book. Basic knowledge of Python and R will also be helpful.
Extending Power BI with Python and R by Luca Zavarella Pdf
Ingest, transform, manipulate, and visualize your data beyond Power BI's capabilities. Purchase of the print or Kindle book includes a free eBook in PDF format. Key Features Discover best practices for using Python and R in Power BI by implementing non-trivial code Enrich your Power BI dashboards using external APIs and machine learning models Create any visualization, as complex as you want, using Python and R scripts Book DescriptionThe latest edition of this book delves deep into advanced analytics, focusing on enhancing Python and R proficiency within Power BI. New chapters cover optimizing Python and R settings, utilizing Intel's Math Kernel Library (MKL) for performance boosts, and addressing integration challenges. Techniques for managing large datasets beyond available RAM, employing the Parquet data format, and advanced fuzzy matching algorithms are explored. Additionally, it discusses leveraging SQL Server Language Extensions to overcome traditional Python and R limitations in Power BI. It also helps in crafting sophisticated visualizations using the Grammar of Graphics in both R and Python. This Power BI book will help you master data validation with regular expressions, import data from diverse sources, and apply advanced algorithms for transformation. You'll learn how to safeguard personal data in Power BI with techniques like pseudonymization, anonymization, and data masking. You'll also get to grips with the key statistical features of datasets by plotting multiple visual graphs in the process of building a machine learning model. The book will guide you on utilizing external APIs for enrichment, enhancing I/O performance, and leveraging Python and R for analysis. You'll reinforce your learning with questions at the end of each chapter.What you will learn Configure optimal integration of Python and R with Power BI Perform complex data manipulations not possible by default in Power BI Boost Power BI logging and loading large datasets Extract insights from your data using algorithms like linear optimization Calculate string distances and learn how to use them for probabilistic fuzzy matching Handle outliers and missing values for multivariate and time-series data Apply Exploratory Data Analysis in Power BI with R Learn to use Grammar of Graphics in Python Who this book is for This book is for business analysts, business intelligence professionals, and data scientists who already use Microsoft Power BI and want to add more value to their analysis using Python and R. Working knowledge of Power BI is required to make the most of this book. Basic knowledge of Python and R will also be helpful.
Extending the Linear Model with R by Julian J. Faraway Pdf
Start Analyzing a Wide Range of Problems Since the publication of the bestselling, highly recommended first edition, R has considerably expanded both in popularity and in the number of packages available. Extending the Linear Model with R: Generalized Linear, Mixed Effects and Nonparametric Regression Models, Second Edition takes advantage of the greater functionality now available in R and substantially revises and adds several topics. New to the Second Edition Expanded coverage of binary and binomial responses, including proportion responses, quasibinomial and beta regression, and applied considerations regarding these models New sections on Poisson models with dispersion, zero inflated count models, linear discriminant analysis, and sandwich and robust estimation for generalized linear models (GLMs) Revised chapters on random effects and repeated measures that reflect changes in the lme4 package and show how to perform hypothesis testing for the models using other methods New chapter on the Bayesian analysis of mixed effect models that illustrates the use of STAN and presents the approximation method of INLA Revised chapter on generalized linear mixed models to reflect the much richer choice of fitting software now available Updated coverage of splines and confidence bands in the chapter on nonparametric regression New material on random forests for regression and classification Revamped R code throughout, particularly the many plots using the ggplot2 package Revised and expanded exercises with solutions now included Demonstrates the Interplay of Theory and Practice This textbook continues to cover a range of techniques that grow from the linear regression model. It presents three extensions to the linear framework: GLMs, mixed effect models, and nonparametric regression models. The book explains data analysis using real examples and includes all the R commands necessary to reproduce the analyses.
Hands-on Intermediate Econometrics Using R: Templates For Extending Dozens Of Practical Examples (With Cd-rom) by Hrishikesh D Vinod Pdf
This book explains how to use R software to teach econometrics by providing interesting examples, using actual data applied to important policy issues. It helps readers choose the best method from a wide array of tools and packages available. The data used in the examples along with R program snippets, illustrate the economic theory and sophisticated statistical methods extending the usual regression. The R program snippets are not merely given as black boxes, but include detailed comments which help the reader better understand the software steps and use them as templates for possible extension and modification.
Hearing in Re H. R, 12343, Extending to the District of Columbia the Act Donating Public Land to the Several States and Territories [December 10, 1909] by United States. Congress. House. Committee on Agriculture Pdf
An Essential Reference for Intermediate and Advanced R Programmers Advanced R presents useful tools and techniques for attacking many types of R programming problems, helping you avoid mistakes and dead ends. With more than ten years of experience programming in R, the author illustrates the elegance, beauty, and flexibility at the heart of R. The book develops the necessary skills to produce quality code that can be used in a variety of circumstances. You will learn: The fundamentals of R, including standard data types and functions Functional programming as a useful framework for solving wide classes of problems The positives and negatives of metaprogramming How to write fast, memory-efficient code This book not only helps current R users become R programmers but also shows existing programmers what’s special about R. Intermediate R programmers can dive deeper into R and learn new strategies for solving diverse problems while programmers from other languages can learn the details of R and understand why R works the way it does.
Advances in Algebra by Jörg Feldvoss,Lauren Grimley,Drew Lewis,Andrei Pavelescu,Cornelius Pillen Pdf
This proceedings volume covers a range of research topics in algebra from the Southern Regional Algebra Conference (SRAC) that took place in March 2017. Presenting theory as well as computational methods, featured survey articles and research papers focus on ongoing research in algebraic geometry, ring theory, group theory, and associative algebras. Topics include algebraic groups, combinatorial commutative algebra, computational methods for representations of groups and algebras, group theory, Hopf-Galois theory, hypergroups, Lie superalgebras, matrix analysis, spherical and algebraic spaces, and tropical algebraic geometry. Since 1988, SRAC has been an important event for the algebra research community in the Gulf Coast Region and surrounding states, building a strong network of algebraists that fosters collaboration in research and education. This volume is suitable for graduate students and researchers interested in recent findings in computational and theoretical methods in algebra and representation theory.
An Information Approach to Mitochondrial Dysfunction by Rodrick Wallace Pdf
The monograph applies sophisticated topological symmetry tools to biological applications of information theory, along with a Black–Scholes model invocation of the Data Rate Theorem which links information and control theories. The focus is on statistical mechanics and other models that explore pathological phase transitions — driven by changes in available rates of mitochondrial free energy — in physiological functions, a cutting-edge topic in the study of chronic disease. One of the key focuses is Alzheimer's disease — a relatively simple canonical example. Contents:Mathematical PreliminariesA Symmetry-Breaking ModelA Data Rate Theorem ModelA Mutual Information ModelA Fragment Size ModelExtending the PerspectiveEmbodiment and EnvironmentChronic InflammationWhat is to be Done?Mathematical Appendix Readership: Graduate students and researchers interested in biological applications of information theory. Key Features:Significantly extends current thinking on Alzheimer's and related chronic diseasesKeywords:Information;Mitochondrial Dysfunction;Black-Scholes Model;Data Rate Theorem
Extending Deontic Logic for the Formalisation of Legal Rules by Lambèr Royakkers Pdf
This book describes extensions of deontic logic. Deontic logic is a branch of philosophical logic involving reasoning with norms, obligations, prohibitions and permissions. The extensions concern the logical structure of legal rules and legal reasoning. Their function is to improve the representation of legal knowledge and enhance deontic logic through increased expressibility. The resulting formulas acquire new meanings, not expressible in standard deontic logic, which are subject to fresh interpretations. The author offers an extensive analysis of the representation of actors, to whom the norms are directed, and authorities who enact the norms. Moreover, a distinction is made between enactment and applicability. A modality of enactment can be used to express inconsistent enacted norms in a consistent way. An authority-hierarchy is introduced to filter out the applicable norms from the set of enacted norms. Some related philosophical questions will be discussed regarding the applications of formalisms that are intrinsic to practical science with respect to `consistency' and `universality'. The formalisms and applications considered here are relevant for law, philosophy and computer science, with a special focus on the improvement of legal expert systems and intelligent support for legal professionals.
