I'm a statistician, data scientist, and lecturer in the Department of Statistics, at UC Berkeley. Professionally, I dedicate most of my time to:

- authoring materials for teaching purposes (books, tutorials, slides, etc.),
- using graphical displays to understand data with visualization,
- applying multivariate methods for exploring, analyzing, and visualizing data in a context of multiple variables and high dimensionality,
- reflecting about computational reproducibility topics and open science,
- and helping researchers and scientists analyze their data.

If you find any value and usefulness in the resources of this site, please consider making a **one-time donation in any amount**. Your support really matters.

Alternatively, you can also help me with my Amazon wishlist.

**Handling Strings with R.**This book aims to help you get started with manipulating strings with R (new bookdown version, work in progress).**Handling and Processing Strings in R**(old pdf version).**Pack YouR Code.**This book aims to help you get started with the creation of a basic R package.**A booklet of R factors.**This little book focuses on the basics, and not so basics, of R factors (work in progress).**A Matrix Algebra Companion for Statistical Learning.**The purpose of this book is to help you understand how statistical notions are connected to matrix algebra concepts that constantly appear around Statistical Learning methods (work in progress).**PLS Path Modeling with R.**This book provides a hands-on introduction to Partial Least Squares Path Modeling (PLS-PM) using the R package "plspm".**The Saga of PLS.**This text narrates the story behind the origins, development, and evolution of Partial Least Squares (PLS) methods.

Some of the courses I've taught in the Department of Statistics, UC Berkeley.

**Stat 2**: Introduction to Statistics**Stat 20**: Introduction to Probability and Statistics**Stat 131A**: Introduction to Probability and Statistics for Life Scientists**Stat 133**: Concepts in Computing with Data**Stat 154**: Modern Statistical Prediction and Machine Learning**Stat 159**: Reproducible and Collaborative Statistical Data Science**Stat 243**: Introduction to Computational Statistics

- Unix basics
- Command Line
- Customizing Bash shell
- Filesystem
- Working with files and directories
- Pipes and redirections

- Introduction
- Classic Examples
- Visualization Basics
- Visual System
- Visual Perception
- What is Color
- Color Vision
- Effective Charts
- Various Examples
- Graphing Process
- Entertainment

- Introduction
- Reading Files from the Web
- Basics of XML and HTML
- Parsing XML / HTML content
- Handling JSON Data
- HTTP Basics and RCurl Package
- Getting Data via Web Forms
- Getting Data via Web APIs

- Introduction
- Various Dependencies
- Various Targets
- Dependent Targets
- File System
- Phony Targets
- Defining Variables
- Automatic Variables
- Wildcard Function
- Pattern Rules
- Pattern Substitutions

- Introduction
- Setting up your PC
- Anatomy of an R package
- Standard (painful) Development
- Building and Checking
- Develop smarter, not harder

I'm a passionate R user as well as developer and maintainer of several R packages. All the code is available in my github repositories.

**plspm**provides a toolkit exclusively dedicated to Partial Least Squares Path Modeling (PLS-PM) analysis.**plsdepot**a set of tools for performing Partial Least Squares (PLS) analysis of one or two data tables.**pathmox**is dedicated to the Pathmox approach for obtaining segmentation trees in Partial Least Squares Path Modeling (PLS-PM) analysis.**arcdiagram**is a minimalist package to help you plot pretty arc diagrams in R.**colortools**is designed to help users generate color schemes and color palettes.**matrixkit**is an R package that provides a first aid kit for some matrix operations commonly used in multivariate data analysis methods.**turner**provides a set of handy functions to turn vectors (and lists of vectors) into other indexed data structures.**tester**provides human readable functions to test characteristics of some common R objects.**cointoss**is a toy package with simple functions for simulating tossing a coin.

Slides of some of my talks.

**Promoting Open Science**(UJAT, Tabasco).**Unconventional Plots in R**(BCC, Berkeley).**Multiblock Dilemas**(McGill University, Montreal).**Arc Diagrams in R**(Bay Area R Users Group).**Thoughts on developing stats software in academia**(LMA Agrocampus, Rennes).**Tips for presentations.**(Oniris, Nantes).**Keep in mind these 5 things ...**(Oniris, Nantes).

**Rtist**: weird but beautiful random paintings.**Got Plot**: tiny collection of polished charts.**Shiny-Introstats**: shiny apps for introduction to statistics.**Star Wars Arc Diagram**: visualizing Star Wars movie scripts.**genbiovis**: deprecated experiment for visualizing titles of genetics & biology papers.**Mining twitter with R**: deprecated experiment that keeps catching people's attention.

Occasionally, I like to talk about data analysis, visualization, statistics, R and related stuff in my blog Data Analysis Visually EnfoRced.

**Fundamentos Teoricos de Maniobras con Cuerdas.**This is a book in Spanish about the theoretical fundamentals of Rope Techniques.**Poemario.**A random collection of personal poems in Spanish.**Quotes.**A curated collection of some of my favorite quotes.