12 citations · 18 across the 7 of their papers we have counts for
9 papers
TEASE: Targeted elastic spatial envelope
Mitchell L. Krock
Envelope regression is a crucial part of multivariate linear modeling, leveraging separation into material and immaterial parts to provide parsimonious data reduction. Rekabdarkola…
Uncertainty quantification for critical energy systems during compound extremes via BMW-GAM
Mitchell L. Krock, W. Neal Mann, Zhi Zhou
Extreme weather poses a large risk to critical energy systems (Ekisheva, Rieder, Norris, Lauby, & Dobson 2021; Levin, Botterud, Mann, Kwon, & Zhou 2022). Uncertainty quantification…
Modeling spatial asymmetries in teleconnected extreme temperatures
Mitchell L. Krock, Julie Bessac, Michael L. Stein
Combining strengths from deep learning and extreme value theory can help describe complex relationships between variables where extreme events have significant impacts (e.g., envir…
Teleconnected warm and cold extremes of North American wintertime temperatures
Mitchell L. Krock, Adam H. Monahan, Michael L. Stein
Current models for spatial extremes are concerned with the joint upper (or lower) tail of the distribution at two or more locations. Such models cannot account for teleconnection p…
Nonstationary seasonal model for daily mean temperature distribution bridging bulk and tails
Mitchell Krock, Julie Bessac, Michael L. Stein +1
In traditional extreme value analysis, the bulk of the data is ignored, and only the tails of the distribution are used for inference. Extreme observations are specified as values…
Modeling massive highly-multivariate nonstationary spatial data with the basis graphical lasso
Mitchell Krock, William Kleiber, Dorit Hammerling +1
We propose a new modeling framework for highly-multivariate spatial processes that synthesizes ideas from recent multiscale and spectral approaches with graphical models. The basis…
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…
Modeling and emulation of nonstationary Gaussian fields
Douglas Nychka, Dorit Hammerling, Mitchell Krock +1
Geophysical and other natural processes often exhibit non-stationary covariances and this feature is important to take into account for statistical models that attempt to emulate t…
Extending Hypothesis Testing with Persistence Homology to Three or More Groups
Christopher Cericola, Inga Johnson, Joshua Kiers +3
We extend the work of Robinson and Turner to use hypothesis testing with persistence homology to test for measurable differences in shape between point clouds from three or more gr…