R: Performs Cross-Validation

xvalid {RGeostats}

R Documentation

Performs Cross-Validation

Description

Cross-validation procedure

Usage

xvalid(db, 
model = model.input(), neigh = neigh.input(), 
uc = c("1"), mean = NA, flag.linked=FALSE,
flag.est=1, flag.std=1, flag.varz=0, flag.code=FALSE,
radix = "Xvalid", modify.target = db.locmod())

Arguments

`db`	The `db-class` structure containing the data file
`model`	The `model-class` structure containing the Model information
`neigh`	The `neigh-class` structure containing the Neighborhood information
`uc`	The drift description. Use command `uc.names` for details.
`mean`	Array containing the mean of each variable, used in the case of Simple (Co-)Kriging
`flag.linked`	When TRUE, the variables are sharing the same mean (or more generally the same drift). Otherwise, the variables have separate means (drifts).
`flag.est`	Define the element based on the estimation stored in the Db: (Z-Z) (if flag.est=1) or Z (if flag.est=-1)
`flag.std`	Define the element based on the standard deviation of estimation error stored in the Db: (Z*-Z)/S (if flag.est=1) or S (if flag.est=-1). Note that S stands for standard deviation of the estimation error
`flag.varz`	Define the element based on the variance of the estomation stored in the Db.
`flag.code`	When ON (and if a "code" variable is defined in 'db'), a sample will be validated using ony samples which do not belong to the same code as the target. This is similar to the K-FOLD option (with no training) of the Machine Learning techniques.
`radix`	Radix of the name given to the variables storing the results in the target Db.
`modify.target`	Decides whether or not the newly created variables will have their locator defined or not. For more information, see `db.locmod`.

Value

The input Db where the following variables have been added. These variables are calculated for each one of the data variables.

[Package RGeostats version 14.0.10 Index]