simcond {RGeostats} | R Documentation |
Conditional Expectation with Inequalities
simcond(dbin, dbout, model = model.input(), seed = 232431, nbsimu = 1, nbtuba = 100, nboot = 10, niter = 100, flag.check = FALSE, flag.ce = FALSE, flag.cstd = FALSE, verbose = FALSE, radix = "SimCond", modify.target = db.locmod())
dbin |
The |
dbout |
The |
model |
The |
seed |
Seed used for the random number generator. When 0, the seed is not initialized. |
nbsimu |
Number of simulations |
nbtuba |
Number of bands used for the internal Turning Bands simulation algorithm |
nboot |
Number of iterations performed for bootstrap |
niter |
Maximum number of iterations for calculating the conditional expectation |
flag.check |
When TRUE, the Gaussian value of the conditional simulation is compared to the value of the closest data. |
flag.ce |
When TRUE, the Conditional Expectation is derived from the simulations |
flag.cstd |
When TRUE, the Conditional Standard Deviation is derived from the simulations |
verbose |
Verbose flag |
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 |
At a constrining sample:
When the lower and the upper bound are provided: the upper bound must be larger than lower bound,
When the lower bound (or the upper bound) is provided alone: the undefined bound is considered as infinite,
When a hard data is provided: this data prevails whether or not the bounds are provided. A warning message is issued is the hard data does not lie between the bounds
When no bound is provided, a message is provided to encourage using simtub() instead of simcond().
The target Db to which several variables have been added:
if 'flag.ce' is specified: the Conditional Expectation variable
if 'flag.cstd' is specified: the Conditional Standard Deviation variable
otherwise, one new variable per simulation