RMmodel
Covariance and Variogram Models in RandomFields
Summary of implemented covariance and variogram models
Details
To generate a covariance or variogram model for use within
...
can take model specific parameters. %Parameter %corresponding to specific covariance modelvar
is the optional variance parameter$v$,scale
the optional scale parameter$s$,Aniso
the optional anisotropy matrix$A$, andproj
is the optional projection vector which defines a diagonal matrix of zeros and ones andproj
gives the positions of the ones (integer values).
Variogram models (stationary increments/intrinsically stationary)
Basic Operations
Basic models for mixed effect modelling
Trend
See RMmodelsAdvanced for many more, advanced models.
References
- Chiles, J.-P. and Delfiner, P. (1999)Geostatistics. Modeling Spatial Uncertainty.New York: Wiley. % \item Gneiting, T. and Schlather, M. (2004) % Statistical modeling with covariance functions. % \emph{In preparation.}
- Schlather, M. (1999)An introduction to positive definite functions and to unconditional simulation of random fields.Technical report ST 99-10, Dept. of Maths and Statistics, Lancaster University.
- Schlather, M. (2011) Construction of covariance functions and unconditional simulation of random fields. In Porcu, E., Montero, J.M. and Schlather, M.,Space-Time Processes and Challenges Related to Environmental Problems.New York: Springer.
- Yaglom, A.M. (1987)Correlation Theory of Stationary and Related Random Functions I, Basic Results.New York: Springer.
- Wackernagel, H. (2003)Multivariate Geostatistics.Berlin: Springer, 3nd edition.
See Also
Examples
set.seed(0)
RFgetModelNames(type="positive definite", domain="single variable",
isotropy="isotropic", operator=FALSE)