Covariances

Theoretical covariances

When variograms reach a finite sill, it is possible to work with equivalent covariance functions. These functions produce numerically stable linear systems, and are preferred by researchers in other scientific fields.

Note

Our Kriging implementation converts variograms into covariances internally (when that is possible) to avoid numerical instabilities. This conversion is efficient thanks to the rich type system, and gives users the freedom to choose whichever function representation they prefer.

Models

GaussianCovariance

funplot(GaussianCovariance())
Example block output

SphericalCovariance

funplot(SphericalCovariance())
Example block output

ExponentialCovariance

funplot(ExponentialCovariance())
Example block output

MaternCovariance

funplot(MaternCovariance())
Example block output

CubicCovariance

funplot(CubicCovariance())
Example block output

PentaSphericalCovariance

funplot(PentaSphericalCovariance())
Example block output

SineHoleCovariance

funplot(SineHoleCovariance())
Example block output

CircularCovariance

funplot(CircularCovariance())
Example block output