  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.
