model.auto {RGeostats}  R Documentation 
Automatic Model Fitting
model.auto(vario, struct = melem.name(c(1,4,5,2,3)), constraints=NA, auth.aniso = TRUE, auth.rotation = TRUE, auth.locksame = FALSE, auth.lock2d = FALSE, flag.goulard=TRUE, flag.noreduce = FALSE, flag.norm.sill=FALSE,flag.keep.intstr=FALSE, param = NA, lower = NA, upper = NA, equal = NA, properties=NA, draw = TRUE, wmode=2, maxiter = 1000, verbose=0, tolstop = 1.e5, epsdelta = 1.e5, tolsigma = 5, delta=1, ...)
vario 
The 
struct 
List of basic structures to be used. It can be given as a vector of
character strings or as a vector of indexes. In the latter case, the
basic structures will be the result of 
constraints 
Vector giving the constraints on the cumulative sills of the model. This vector must be dimensionned to the number of variables in the variogram. All the defined terms must be positive (or undefined). Otherwise, no constraints is applied on the Sill estimation. This is incompatible with the 'flag.norm.sill' flag. 
auth.aniso 
When TRUE, the anisotropy will be checked 
auth.rotation 
When TRUE, the fit will look for rotation search in anisotropy. However note that an initial rotation is always defined (based on the calculation directions of the experimental variogram). Therefore when this switch is OFF, the initial rotation is maintained. 
auth.locksame 
When TRUE and if an anisotropy is allowed (auth.aniso), all the basic structures should share the same rotation. 
auth.lock2d 
When TRUE, the anisotropy rotation will only consider a rotation around the Zaxis. The Dip and Plunge angles are kept equal to zero. 
flag.goulard 
When TRUE, the Goulard algorithm is used for the determination of the Sills (quicker). Otherwise Sills are infered using the standard Foxleg algorithm. 
flag.noreduce 
When TRUE, the useless basic structures must not be discarded. 
flag.norm.sill 
When TRUE, the automatic fit must fulfill the constraint that the sum of the sills must always be equal to 1. This flag is incompatible with the definition of 'constraints'. 
flag.keep.intstr 
When TRUE, the fitting procedure must always maintain at least one intrinsic basic structure. If no intrinsic basic structure is provided in the initial template, the automatic fitting procedure fails. 
param 
List of initial values for the parameters to be fitted.
For details see 
lower 
List of lower bounds for the parameters to be fitted
For details see 
upper 
List of upper bounds for the parameters to be fitted
For details see 
equal 
List of constant values assigned to the parameters to be fitted
For details see 
properties 
This argument defines the transformation to be applied to the model.
For more details, see 
draw 
When TRUE, both the experimental variograms and the Model are represented graphically. Otherwise, no graphic is produced. 
wmode 
Type of the weighting function used in the fitting procedure. This function is defined in the case of several directional experimental variograms, calculated in a multivariate case:

maxiter 
Maximum number of iterations 
verbose 
Verbose option

tolstop 
Tolerance for the distance between the experiment and the model. 
epsdelta 
Tolerance for the direction increment used in the gradient search 
tolsigma 
Percentage of the variance below which a basic structure will be discarded 
delta 
Delta value 
... 
Arguments passed to 
The modelclass
with fitted parameters
When needed, you can access to each matrix of sills by using the keypair mechanism using the keyword "Fitted_Sill_'i'" where 'i' stands for the rank of the each basic structure (starting from 1).
You can also access to the eigen decomposition of the matrix of Sills of rank 'i' where 'i' stands for the rank of each basic structure (starting from 1), using:
Model_Auto_Eigen_Values_'i' for the eigen values (Dim: nvar)
Model_Auto_Eigen_Vector_'i' for the eigen vectors (Dim: nvar*nvar)
Function originally funded by Geovariances and ANR CRISCO2.
Nicolas Desassis and Didier Renard (Geosciences/MinesParisTech)
data(Exdemo_autofit3.vario) plot(Exdemo_autofit3.vario, title="Experimental Variogram in 2D space to be Fitted") model < model.auto(Exdemo_autofit3.vario,maxiter=100, title="Experimental variogram in 2D space") rm(model,pos=1)