activity
20152020
most citedStochastic Tropical Cyclone Precipitation Field Generation

2 citations · 3 across the 5 of their papers we have counts for

collaborators

5 papers

stat.AP20202 cited

Stochastic Tropical Cyclone Precipitation Field Generation

William Kleiber, Stephan Sain, Luke Madaus +1

Tropical cyclones are important drivers of coastal flooding which have severe negative public safety and economic consequences. Due to the rare occurrence of such events, high spat…

stat.ME2020

Nonrigid registration using Gaussian processes and local likelihood estimation

Ashton Wiens, William Kleiber, Douglas Nychka +1

Surface registration, the task of aligning several multidimensional point sets, is a necessary task in many scientific fields. In this work, a novel statistical approach is develop…

stat.ME2020

Modeling spatial data using local likelihood estimation and a Matérn to SAR translation

Ashton Wiens, Douglas Nychka, William Kleibe

Modeling data with non-stationary covariance structure is important to represent heterogeneity in geophysical and other environmental spatial processes. In this work, we investigat…

stat.ME20191 cited

Penalized basis models for very large spatial datasets

Mitchell Krock, William Kleiber, Stephen Becker

Many modern spatial models express the stochastic variation component as a basis expansion with random coefficients. Low rank models, approximate spectral decompositions, multireso…

math.ST2015

Coherence for Random Fields

William Kleiber

Multivariate spatial field data are increasingly common and whose modeling typically relies on building cross-covariance functions to describe cross-process relationships. An alter…