6 papers
A Physically-Motivated Stochastic Model of Tropical Cyclone Dynamic Wind Fields
Matthew LeDuc, William Kleiber
Tropical cyclones (TCs) pose significant risk to infrastructure and human safety, and the frequency and intensity of large TCs are expected to increase in the future. Quantifying s…
Calibration Assessment for Nested Uncertainty Sets
Matthew LeDuc
We present a Bayesian framework for assessing the calibration of nested uncertainty sets from simulation studies. Calibration is typically evaluated by repeatedly simulating data f…
An RKHS Framework for Fixed Effects in Permanental Process Models
Matthew LeDuc
This short work describes an extension of the permanental process model which includes fixed effects. By starting with a prior on the fixed effects coefficients we show that, in th…
The Continuous Rank Probability Score of a Generalized Beta-Prime Distribution and Some Special Cases
Matthew LeDuc
This working paper describes new results in derivations of the Continuous Ranked Probability Score of a generalized beta-prime distribution and several special cases, such as the D…
PoissonRatioUQ: An R package for band ratio uncertainty quantification
Matthew LeDuc, Tomoko Matsuo
We introduce an R package for Bayesian modeling and uncertainty quantification for problems involving count ratios. The modeling relies on the assumption that the quantity of inter…
Modeling Large Nonstationary Spatial Data with the Full-Scale Basis Graphical Lasso
Matthew LeDuc, William Kleiber, Tomoko Matsuo
We propose a new approach for the modeling large datasets of nonstationary spatial processes that combines a latent low rank process and a sparse covariance model. The low rank com…