Beginning R4

Learn how to use R 4, write and save R scripts, read in and write out data files, use built-in functions, and understand common statistical methods. This in-depth tutorial includes key R 4 features including a new color palette for charts, an enhanced reference counting system (useful for big data), and new data import settings for text (as well as the statistical methods to model text-based, categorical data). View GitHub Code.

Data Programming and the Cloud 2nd Ed.

Advanced R 4 Data Programming and the Cloud 2nd Edition is designed to be a practical guide moving beyond merely using R; it shows you how to program in R to automate tasks. This book will teach you how to manipulate data in modern R structures and includes connecting R to databases such as PostgreSQL, cloud services such as Amazon Web Services (AWS), and digital dashboard such as Shiny. View GitHub Code.

Statistical Programming and Data Models 1st Ed.

Carry out a variety of advanced statistical analyses including generalized additive models, mixed effects models, multiple imputation, machine learning, and missing data techniques using R. Each chapter starts with conceptual background information about the techniques, includes multiple examples using R to achieve results. View GitHub Code.

Data Programming and the Cloud 1st Ed.

Now updated - see above!This book will show you how to manipulate data in modern R structures and includes connecting R to data bases such as SQLite, PostgeSQL, and MongoDB. The book closes with a hands-on section to get R running in the cloud. Each chapter also includes a detailed bibliography with references to research articles and other resources that cover relevant conceptual and theoretical topics. View GitHub Code.

Reviewed Book

This extraordinarily well-crafted resource provides accessible pseudocode along with rigorous proofs, and of course C++ implementations, of highly relevant and modern assessment of prediction and classification efficacy.

Reviewed Book