likely llc

quantitative consulting

appointments

Statistician – University of Michigan Department of Cardiovascular Medicine


selected works

The Tampa Bay Rays – Bayesian statistical models to forecast player performance.

The University of Michigan Department of Cardiovascular Medicine – Analysis of omics data, other biomedical data analysis, clinical data.

about

Andre Zapico – Andre has recently been granted a position as a part-time statistician at the University of Michigan in the Department of Cardiovascular medicine to work on the analysis of omics data. He completed his masters in engineering at the University of Electronic Science and Technology of China in Information and Communication Engineering in 2021 with graduate level mathematics course work. His undergraduate dual degree is in the mathematical sciences and statistics from the University of Michigan Ann Arbor in 2017. He is also a member of the stan development team. He focuses on applied statistics, maths and programming for research. linkedin, github

blog

Models, Algorithms and Software for Statistical Inference

I’m often asked by recruiters, clients, academics or colleagues which models I’ve worked with. This post is an effort to put this all in one place. All of these models, algorithms, and software I’ve worked with in some capacity. This includes implementation, development, application, required understanding, or any combination thereof. This list in non-exhaustive. I’ll […]

So What Actually Happened in Finland? Aalto University Internship Summer 2018, Part 1

After working in the psychiatry department at Michigan, I worked at Aalto University in Espoo, Finland next summer. There, I worked on the Stan math library implementing Gaussian process covariance functions and matrix utilities to make Gaussian process models more feasible in Stan. The ultimate goal was to implement what’s known as “the birthday problem” […]

Clustering Using SVD on Omics Data

For Michigan, I’ve since applied the SVD based sorting algorithm, which can be used for clustering, to real data. The goal is to in some way model the relationship of proteins and metabolites, come up with modules, or groups of proteins and metabolites that were related, and then use these later in a regression model […]

Additive Gaussian Process Time Series Regression in Stan

I’ve copied this over from discourse.mc-stan.org, but this was my post, so I’m comfortable doing so. While working in the psychiatry department at Michigan, I played around with EEG data. Next, I became curious about how to extract out different periodic components of a time series. I ended up finding a blog post on Andrew […]

My Work at the University of Michigan Psychiatry Department in 2017, Part 1

After I finished my undergraduate degree at the University of Michigan in 2017, in the Mathematical Sciences, and Statistics, I worked in the University of Michigan Psychiatry Department. This was with Daniel Kessler, Dr. Eunjee Lee, Dr. Chandra Sripada, and Mike Angstadt. This was in 2017, so thank you for understanding if vocab isn’t up […]

Clustering Using SVD

Dr. Murthy and I have been working on a way to interpret omics data. We’d like to see if there’s any natural grouping structure to a large dataset. We’ve computed something resembling a cross covariance matrix. After Dr. Murthy experimented with sparse CCA for a while, we tried some other clustering methods or regularization methods […]

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