9 papers
Collaborative estimation and evaluation of SARS-CoV-2 variant nowcasting in the United States
Isaac MacArthur, Thomas Robacker, Bren Case +27
The ability to estimate and predict pathogen variant dynamics can inform public health responses, including planning for increased transmission or severity, shifts in population im…
A Simple Approach for Local and Global Variable Importance in Nonlinear Regression Models
Emily T. Winn-Nuñez, Maryclare Griffin, Lorin Crawford
The ability to interpret machine learning models has become increasingly important as their usage in data science continues to rise. Most current interpretability methods are optim…
Improved Pathwise Coordinate Descent for Power Penalties
Maryclare Griffin
Pathwise coordinate descent algorithms have been used to compute entire solution paths for lasso and other penalized regression problems quickly with great success. They improve up…
Log-Gaussian Cox Process Modeling of Large Spatial Lightning Data using Spectral and Laplace Approximations
Megan L. Gelsinger, Maryclare Griffin, David S. Matteson +1
Lightning is a destructive and highly visible product of severe storms, yet there is still much to be learned about the conditions under which lightning is most likely to occur. Th…
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 $…
Modeling a Nonlinear Biophysical Trend Followed by Long-Memory Equilibrium with Unknown Change Point
Wenyu Zhang, Maryclare Griffin, David S. Matteson
Measurements of many biological processes are characterized by an initial trend period followed by an equilibrium period. Scientists may wish to quantify features of the two period…
Structured Shrinkage Priors
Maryclare Griffin, Peter D. Hoff
In many regression settings the unknown coefficients may have some known structure, for instance they may be ordered in space or correspond to a vectorized matrix or tensor. At the…
Testing Sparsity-Inducing Penalties
Maryclare Griffin, Peter D. Hoff
Many penalized maximum likelihood estimators correspond to posterior mode estimators under specific prior distributions. Appropriateness of a particular class of penalty functions…
Lasso ANOVA Decompositions for Matrix and Tensor Data
Maryclare Griffin, Peter D. Hoff
Consider the problem of estimating the entries of an unknown mean matrix or tensor given a single noisy realization. In the matrix case, this problem can be addressed by decomposin…