mra (version 2.3)

mra.control: mra.control - Control over MRA fitting process

Description

Auxiliary function providing a user interface for mra fitting. Typically only used when calling one of the *.estim routines.

Usage

mra.control(algorithm=1, maxfn=1000, cov.meth=1, trace=0, tol=1e-07 )

Arguments

algorithm

Integer specifying the maximization algorithm to use. If algorithm = 1, the VA09AD algorithm from the HSL library is used. The VA09AD algorithm is very reliable, has been tested extensively (same algorithm as Program MARK), and w

maxfn

Maximum number of likelihood evaluations allowed during the fitting process. This determines when the minimization routine stops and concludes that the problem will not converge. The routine stops after the likelihood has been evaluated

cov.meth

Integer specifying the covariance estimation method. cov.meth = 1 takes numerical 2nd partial derivatives. cov.meth = 2 inverts the Hessian of the maximization. Method 1 (numeric 2nd derivatives) is the preferred me

trace

Integer controling output of intermediate results. If trace != 0, a few lines will be written to the R console and a log file (named mra.log) will be opened in the current directory and details of the fitting process

tol

Vector or scalar of tolerance(s) for coefficients in the model. Minimization stops and concludes it has converged when |delta.b(i)| < tol(i) for all i, where delta.b(i) is change in parameter i on an iteration.

Value

• A list with the input arguments as components.

See Also

F.cjs.estim, F.huggins.estim

Examples

data(dipper.histories)
ct <- as.factor( paste("T",1:ncol(dipper.histories), sep=""))
attr(ct,"nan")<-nrow(dipper.histories)
dipper.cjs <- F.cjs.estim( ~tvar(ct,drop=c(1,2)), ~tvar(ct,drop=c(1,6,7)), dipper.histories, control=mra.control(trace=1, maxfn=200) )