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20162026
most citedModeling massive highly-multivariate nonstationary spatial data with the basis graphical lasso

12 citations · 18 across the 7 of their papers we have counts for

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7 papers · 1 filter

stat.ME2026

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…

stat.ME2026

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…

stat.ME2022★ 1 cited

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…

stat.ME2021★ 12 cited

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…

stat.ME2019★ 1 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…

stat.ME2017

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…

stat.ME2016★ 4 cited

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…