An overview of KrigingModel classes
The KrigingModel classes define the kriging method and its parameters that will be used in a kriging interpolation. There are two kriging methods: ordinary and universal.
Ordinary kriging is the most general and widely used of the kriging methods and is the default. It assumes the constant mean is unknown. This is a reasonable assumption unless there is a scientific reason to reject it.
Universal kriging assumes that the spatial variation in zvalues is the sum of three components: a structural component (drift), a random but spatially correlated component, and a random noise representing the residual error. The structural component represents a constant trend over the surface. The random noise is assumed to be spatially independent and have a normal distribution. Once the structural effects have been accounted for, the remaining variation is spatially homogeneous such that the zvalue difference between input sample points is merely a function of the distance between them as with ordinary kriging.
Defines the Ordinary Kriging model. The available model types are Spherical, Circular, Exponential, Gaussian, and Linear. 

Defines the Universal Kriging model. The available model types are Linear with linear drift and Linear with quadratic drift. 
The tool that uses kriging objects