gibbs {RGeostats}R Documentation

Perform simulations using the Gibbs Sampler

Description

Perform simulations using gibbs sampler

Usage

gibbs(db = NA, model = model.input(), seed = 232131, nbsimu = 1, rank.grf = 1, 
	 nboot = 10, niter = 100, flag.norm=FALSE, flag.propagation=FALSE,
	 nostat=NA, percent=0.1, toleps = 1, 
	 radix = "Gibbs", modify.target = db.locmod())

Arguments

db

The db-class structure containing the lower and upper bounds (expressed in gaussian scale).

model

The model-class structure containing the Model information

seed

Seed used for the random number generator. When 0, the seed is not initialized.

nbsimu

Number of simulations

rank.grf

Rank of the gaussian random function to be simulated

nboot

Number of iterations performed for bootstrap

niter

Maximum number of iterations for calculating the conditional expectation

flag.norm

When TRUE, the model is normalized (as it should correspond to a normalized gaussian).

flag.propagation

When TRUE, the Gibbs sampler using the propagation algorithm is used. This method is incompatible with the presence of bounds.

nostat

List of non-stationary parameters. For details see model.param.define.

percent

Amount of nugget effect added to the model if this initial model only contains Gaussian structures. If set to zero, the initial model is kept unchanged. This amount is defined as a percentage of the global variance.

toleps

Relative difference between the previous and the new value at a sample location below which the sample is considered as immobile

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.

Details

Some parameters are passed by the 'keypair' mechanism (in the case of Gibbs Propagation algorithm):

Value

The data Db where the simulated variable has been added


[Package RGeostats version 11.0.6 Index]