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Engineering Production-grade Shiny Apps
"Presented in full color, Engineering Production-Grade Shiny Apps helps people build production-grade shiny applications, by providing advice, tools, and a methodology to work on web applications with R. This book starts with an overview of the challenges which arise from any big web application project: organizing work, thinking about the user interface, challenges of teamwork & production environment. Then, it moves to a step by step methodology that goes from the idea to the end application. Each part of this process will cover in detail a series of tools and methods to use while building production-ready shiny applications. Finally, the book will end with a series of approaches and advice about optimizations for production"--
Learn R
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 ...
Deep Learning and Scientific Computing with R torch
torch is an R port of PyTorch, one of the two most-employed deep learning frameworks in industry and research. It is also an excellent tool to use in scientific computations. It is written entirely in R and C/C++. Though still "young" as a project, R torch already has a vibrant community of users and developers. Experience shows that torch users come from a broad range of different backgrounds. This book aims to be useful to (almost) everyone. Globally speaking, its purposes are threefold: - Provide a thorough introduction to torch basics – both by carefully explaining underlying concepts and ideas, and showing enough examples for the reader to become "fluent" in torch. - Again with a focu...
A Criminologist's Guide to R
A Criminologist's Guide to R: Crime by the Numbers introduces the programming language R and covers the necessary skills to conduct quantitative research in criminology. By the end of this book, a person without any prior programming experience can take raw crime data, be able to clean it, visualize the data, present it using R Markdown, and change it to a format ready for analysis. A Criminologist's Guide to R focuses on skills specifically for criminology such as spatial joins, mapping, and scraping data from PDFs, however any social scientist looking for an introduction to R for data analysis will find this useful. Key Features: Introduction to RStudio including how to change user preference settings. Basic data exploration and cleaning – subsetting, loading data, regular expressions, aggregating data. Graphing with ggplot2. How to make maps (hotspot maps, choropleth maps, interactive maps). Webscraping and PDF scraping. Project management – how to prepare for a project, how to decide which projects to do, best ways to collaborate with people, how to store your code (using git), and how to test your code.
Spatial Sampling with R
Scientific research often starts with data collection. However, many researchers pay insufficient attention to this first step in their research. The author, researcher at Wageningen University and Research, often had to conclude that the data collected by fellow researchers were suboptimal, or in some cases even unsuitable for their aim. One reason is that sampling is frequently overlooked in statistics courses. Another reason is the lack of practical textbooks on sampling. Numerous books have been published on the statistical analysis and modelling of data using R, but to date no book has been published in this series on how these data can best be collected. This book fills this gap. Spati...
Rasch Measurement Theory Analysis in R
Rasch Measurement Theory Analysis in R provides researchers and practitioners with a step-by-step guide for conducting Rasch measurement theory analyses using R. It includes theoretical introductions to major Rasch measurement principles and techniques, demonstrations of analyses using several R packages that contain Rasch measurement functions, and sample interpretations of results. Features: Accessible to users with relatively little experience with R programming Reproducible data analysis examples that can be modified to accommodate users’ own data Accompanying e-book website with links to additional resources and R code updates as needed Features dichotomous and polytomous (rating scal...
Model-Based Clustering, Classification, and Density Estimation Using mclust in R
Model-Based Clustering, Classification, and Denisty Estimation Using mclust in R Model-based clustering and classification methods provide a systematic statistical approach to clustering, classification, and density estimation via mixture modeling. The model-based framework allows the problems of choosing or developing an appropriate clustering or classification method to be understood within the context of statistical modeling. The mclust package for the statistical environment R is a widely adopted platform implementing these model-based strategies. The package includes both summary and visual functionality, complementing procedures for estimating and choosing models. Key features of the b...
Mastering Shiny
Master the Shiny web framework—and take your R skills to a whole new level. By letting you move beyond static reports, Shiny helps you create fully interactive web apps for data analyses. Users will be able to jump between datasets, explore different subsets or facets of the data, run models with parameter values of their choosing, customize visualizations, and much more. Hadley Wickham from RStudio shows data scientists, data analysts, statisticians, and scientific researchers with no knowledge of HTML, CSS, or JavaScript how to create rich web apps from R. This in-depth guide provides a learning path that you can follow with confidence, as you go from a Shiny beginner to an expert developer who can write large, complex apps that are maintainable and performant. Get started: Discover how the major pieces of a Shiny app fit together Put Shiny in action: Explore Shiny functionality with a focus on code samples, example apps, and useful techniques Master reactivity: Go deep into the theory and practice of reactive programming and examine reactive graph components Apply best practices: Examine useful techniques for making your Shiny apps work well in production
ANOVA and Mixed Models
ANOVA and Mixed Models: A Short Introduction Using R provides both the practitioner and researcher a compact introduction to the analysis of data from the most popular experimental designs. Based on knowledge from an introductory course on probability and statistics, the theoretical foundations of the most important models are introduced. The focus is on an intuitive understanding of the theory, common pitfalls in practice, and the application of the methods in R. From data visualization and model fitting, up to the interpretation of the corresponding output, the whole workflow is presented using R. The book does not only cover standard ANOVA models, but also models for more advanced designs...
Outstanding User Interfaces with Shiny
Outstanding User Interfaces with Shiny provides the reader with necessary knowledge to develop beautiful and highly interactive user interfaces. It gives the minimum requirements in HTML/JavaScript and CSS to be able to extend already existing Shiny layouts or develop new templates from scratch. Suitable for anyone with some experience of Shiny, package development and software engineering best practices, this book is an ideal guide for graduates and professionals who wish to bring their app design to the next level. Key Features: Provides a survival kit in web development to seamlessly get started with HTML/CSS/JavaScript Leverage CSS and Sass and higher-level tools like {bslib} to substant...
