Position of the parameters

Description

The function returns the internal positions of the model parameters

Usage

  parampositions(model, param, print=TRUE)

Arguments

Value

The model is printed and returned where the values of the parameters are the positions in the internal representation.
An error appears if the model can be substantially simplified.

Author(s)

Martin Schlather, martin.schlather@math.uni-goettingen.de http://www.stochastik.math.uni-goettingen.de/institute

See Also

CovarianceFct, fitvario

Examples

## compare the output of the following commands
parampositions(model="exp", param=c(0,1,0,NA))
parampositions(model="exp", param=c(0,1,NA,NA)) 
parampositions(model="exp", param=c(0,0,1,NA)) 
## that is, the nugget in the standard model is removed if naught!
## the values of the other parameters do not matter. (First value
## of the returned vector refers to the mean position.)

parampositions(model="whi", param=cbind(c(1, 1, 1), c(2, 2, 2)))
parampositions(model="whi", param=cbind(c(1, 1, 1), c(2, 0, 2)))
## second lines, second column defines a nugget effect since scale is 0!

try(parampositions(model="whi", param=cbind(c(1, 1, 1), c(0, 0, 0))))
## leads to an error

try(parampositions(model="whi",
                   param=cbind(c(1, 1, 1), c(2, 0, 0), c(1, 0, 0)))) 
## leads to an error

try(parampositions(model="whi",
                   param=cbind(c(1, 1, 1), c(NA, 0, 0), c(1, 0, 0))))
## leads to an error

parampositions(model=list(list(model="exp", var=3, scale=6), "+",
                           list(model="whittle", var=2, scale=7,
                                kappa=NA))) ## again the values do not matter