Welcome!

Welcome and thank you for visiting my personal website! I’m J. Steven Raquel and I have a Master of Science in Statistics degree from the University of California, Irvine.

Find out more about who I am and what I’ve done.

If you know anything about statistics, biostatistics, machine learning, epidemiology, or public health, feel free to get in touch with me! I have a lot to learn so I’m eager to touch base with folks with similar interests. You can find my email, GitHub and LinkedIn under Contact Me in the header.

Projects

These are some of the projects I’ve worked on throughout my time studying statistics, and I am constantly learning and adding things to my repertoire.

This paper was written for STATS 255 Survival Analysis and models human serum albumin’s relationship with the survival of end-stage renal disease patients, both as a static and time-varying covariate.

This paper was written for STATS 295 Spatial Statistics and showcases the usage of a Matern cluster point process to model the incidence of gun violence in K-12 schools between the years of 1990-2019.

This paper was written for Sociology 280 and uses exponential random graph modeling to model (and simulate) the ties of a sexual social network in an indigenous community in Alberta, Canada, in which a gonorrhea outbreak had occurred.

For my final project for Statistics 131 Data Mining, I used and compared the decision tree, randomForest and k-Nearest Neighbors algorithms using R to determine the quality of a wine and what the best algorithm was for classification. I also came to determine what attributes were most important towards a good wine.

This project utilizes various regression algorithms including ordinary least squares regression, decision trees, random forests, k-nearest neighbors, and gradient boosting in Python to create a regression model using various attributes of the housing market in Boston.

For my final project in PSTAT 147 Time Series, I attempted to apply the Box-Jenkins ARIMA model using R to several observations of the opening price of the cryptocurrency known as bitcoin. It turned out that the variability of the data was too sporadic and unpredictable, and ultimately I concluded that the GARCH model was most likely better because it accounts for the heteroskedasticity. While I did not fit that GARCH model I did fit a couple of ARIMA models and forecasted with them.

Packages and Shiny Apps

Together with my partner Pin-Chun Chen, we designed an R package called ggomoku that allowed you to play the board game Gomoku. The source code for the package can be found on GitHub.

We later ported this game over to the Shiny framework in R, which allowed the game to be playable on the web without loading the package in R. It’s deployed on shinyapps.io. The source code for this Shiny app can be found on GitHub.