I'm an applied statistician, data scientist, and faculty member in the Department of Statistics, at UC Berkeley.

Among other things, I am very interested in:

- multivariate methods for exploring, analyzing, and visualizing data in a context of multiple variables and high dimensionality.
- the use of graphical displays to understand data with visualization.
- topics about computational reproducibility and open science.
- helping researchers and scientists analyze their data.

I am serious about **Open Science** and **Open Knowledge**; sincerely committed to the principle that everything I produce—tutorials, slides, teaching materials, software, data—should be immediately freely accessible for anyone to access, download, use, and extend upon it.

This website is my personal space where I try to declutter my ideas and put
all my work in order (which is easier said than done). If you find any valuable
resources here (which I'm pretty sure you will) please consider giving something back
from my **wishlist**.

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

- Introduction
- Reading Files from the Web
- Basics of XML and HTML
- Parsing XML / HTML content
- Hanlding 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

**Stat 2**: Introduction to Statistics**Stat 20/131A**: Introduction to Probability and Statistics**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

**Handling Strings in R.**This book aims to help you get started with manipulating strings in R (new bookdown version).**Handling Strings in R**(old pdf version).**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.**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..

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.

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**polished charts.**Shiny-Introstats**: shiny apps for introduction to statistics.**Star Wars Arc Diagram**: visualizaing Star Wars movie scripts.

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