Publications

Taylor R. Brown (2022). A Case-Study of Sample-Based Bayesian Forecasting Algorithms.

Bruce A. Corliss, Taylor R. Brown, Tingting Zhang, Kevin A. Janes, Heman Shakeri, Philip E. Bourne (2022). The Most Difference in Means: A Statistic for Null and Near-Zero Results.

Taylor R. Brown (2021). An Introduction to R and Python For Data Analysis: A Side By Side Approach.

Taylor R. Brown (2020). A Short Introduction to PF: A C++ Library for Particle Filtering.

Taylor R. Brown (2020). Approximating Posterior Predictive Distributions by Averaging Output From Many Particle Filters.

Taylor R. Brown (2020). PF: A C++ Library for Fast Particle Filtering.

Taylor R. Brown, Timothy L. McMurry, Alexander Langevin (2019). A Pseudo-Marginal Metropolis-Hastings Algorithm for Estimating Generalized Linear Models in t he Presence of Missing Data.

Taylor R. Brown (2019). A Factor Stochastic Volatility Model with Markov-Switching Panic Regimes.

Taylor Brown (2018). Factor Stochastic Volatility Models for Portfolio Construction.