8 citations · 15 across the 11 of their papers we have counts for
4 papers · 1 filter
A multi-stage Bayesian approach to fit spatial point process models
Rachael Ren, Mevin B. Hooten, Toryn L. J. Schafer +4
Spatial point process (SPP) models are commonly used to analyze point pattern data in many fields, including presence-only data in ecology. Existing exact Bayesian methods for fitt…
Locally Adaptive Shrinkage Priors for Trends and Breaks in Count Time Series
Toryn L. J. Schafer, David S. Matteson
Non-stationary count time series characterized by features such as abrupt changes and fluctuations about the trend arise in many scientific domains including biophysics, ecology, e…
Drift vs Shift: Decoupling Trends and Changepoint Analysis
Haoxuan Wu, Toryn L. J. Schafer, Sean Ryan +1
We introduce a new approach for decoupling trends (drift) and changepoints (shifts) in time series. Our locally adaptive model-based approach for robustly decoupling combines Bayes…
Trend and Variance Adaptive Bayesian Changepoint Analysis & Local Outlier Scoring
Haoxuan Wu, Toryn L. J. Schafer, David S. Matteson
We adaptively estimate both changepoints and local outlier processes in a Bayesian dynamic linear model with global-local shrinkage priors in a novel model we call Adaptive Bayesia…