5 papers
Modeling Dynamic Correlation Matrices with Shrinkage Priors
Daniel Andrew Coulson, David S. Matteson, Martin T. Wells
Estimating time-varying correlation matrices is challenging because existing methods may adapt slowly to structural changes, impose insufficient regularization, or produce diffuse…
Smoothing Variances Across Time: Adaptive Stochastic Volatility
Jason B. Cho, David S. Matteson
We introduce a novel Bayesian framework for estimating time-varying volatility by extending the Random Walk Stochastic Volatility (RWSV) model with Dynamic Shrinkage Processes (DSP…
Testing Simultaneous Diagonalizability
Yuchen Xu, Marie-Christine Düker, David S. Matteson
This paper proposes novel methods to test for simultaneous diagonalization of possibly asymmetric matrices. Motivated by various applications, a two-sample test as well as a genera…
Bayesian changepoint detection via logistic regression and the topological analysis of image series
Andrew M. Thomas, Michael Jauch, David S. Matteson
We present a Bayesian method for multivariate changepoint detection that allows for simultaneous inference on the location of a changepoint and the coefficients of a logistic regre…
Likelihood Inference for Possibly Non-Stationary Processes via Adaptive Overdifferencing
Maryclare Griffin, Gennady Samorodnitsky, David S. Matteson
We make an observation that facilitates exact likelihood-based inference for the parameters of the popular ARFIMA model without requiring stationarity by allowing the upper bound $…