20 citations · 20 across the 4 of their papers we have counts for
4 papers
BASTION: A Bayesian Framework for Trend and Seasonality Decomposition
Jason B. Cho, David S. Matteson
We introduce BASTION (Bayesian Adaptive Seasonality and Trend DecompositION), a flexible Bayesian framework for decomposing time series into trend and multiple seasonality componen…
Dynamic Bayesian Item Response Model with Decomposition (D-BIRD): Modeling Cohort and Individual Learning Over Time
Hansol Lee, Jason B. Cho, David S. Matteson +1
We present D-BIRD, a Bayesian dynamic item response model for estimating student ability from sparse, longitudinal assessments. By decomposing ability into a cohort trend and indiv…
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…
Non-fungible token transactions: data and challenges
Jason B. Cho, Sven Serneels, David S. Matteson
Non-fungible tokens (NFT) have recently emerged as a novel blockchain hosted financial asset class that has attracted major transaction volumes. Investment decisions rely on data a…