A Nonstationary Designer Space-Time Kernel
Computation
2018-12-04 v1 Numerical Analysis
Abstract
In spatial statistics, kriging models are often designed using a stationary covariance structure; this translation-invariance produces models which have numerous favorable properties. This assumption can be limiting, though, in circumstances where the dynamics of the model have a fundamental asymmetry, such as in modeling phenomena that evolve over time from a fixed initial profile. We propose a new nonstationary kernel which is only defined over the half-line to incorporate time more naturally in the modeling process.
Cite
@article{arxiv.1812.00173,
title = {A Nonstationary Designer Space-Time Kernel},
author = {Michael McCourt and Gregory Fasshauer and David Kozak},
journal= {arXiv preprint arXiv:1812.00173},
year = {2018}
}
Comments
5 pages, 2 figures, NIPS 2018 spacetime workshop