arXiv · 1505.07710
Bayesian Trend Filtering
Abstract
We develop a fully Bayesian hierarchical model for trend filtering, itself a new development in nonparametric, univariate regression. The framework more broadly applies to the generalized lasso, but focus is on Bayesian trend filtering. We compare two shrinkage priors, double exponential and generalized double Pareto. A simulation study, comparing Bayesian trend filtering to the original formulation and a number of other popular methods shows our method to improve estimation error while maintaining if not improving coverage probability. Two time series data sets demonstrate Bayesian trend filtering's robustness to possible violations of its assumptions.
Explore related subjects
Keep this discovery
Edward A. Roualdes. 2015-05-28. Bayesian Trend Filtering. https://arxiv.org/abs/1505.07710
Cite the original work for its findings. Save a collection to share your selection of sources.