likely llc

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  • 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 […]

    likelyandre

    September 3, 2022
    Uncategorized
  • 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” […]

    likelyandre

    August 24, 2022
    Uncategorized
    autodiff, bayes, gaussianprocesses, MCMC, optimization, stan, statistics
  • 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 […]

    likelyandre

    August 11, 2022
    Uncategorized
    applied math, linearalgebra, machinelearning, metabolites, omics, proteins, R, statistics, svd
  • Multilevel Gaussian Processes to Model Hit Speed in Baseball

    This is a practice test I was given prior to landing a contract with the Tampa Bay Rays from July 2021. Here, I was asked to predict hit speed given angle off the bat. There’s a publicly available github repository with the same data here: https://github.com/danhogan/batted-ball. Below is copied from the practice test. This is […]

    likelyandre

    August 8, 2022
    Uncategorized
  • 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 […]

    likelyandre

    August 3, 2022
    Uncategorized
    bayesian, gaussianprocesses, stan, statistical modeling, statistics
  • 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 […]

    likelyandre

    August 2, 2022
    Uncategorized
    bayesian, dimension reduction, fMRI, MCMC, statistical modeling, statistics, svd
  • 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 […]

    likelyandre

    June 13, 2022
    Uncategorized
    applied math, clustering, R, statistics, svd

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