Finds optimum within a region

Usage

optim.funfits(fit, start, maximize=T, lower, upper, ...)

Arguments

fit Object from a fitting procedure. A predict function for the fit must be available.
start Starting value for the search, the default is the middle of the region.
maximize Default is to search for the maximum.
lower Lower bound of parameters for optimization, default is the minimum of the data.
upper Upper bound of parameters for optimization, default is the maximum of the data.
... Optional arguments.

Description

The object from a fitting procedure must have a predict function. Optim calls the function nlminb which finds a local minimum of a smooth nonlinear function subject to bounded-constrained paramenters.

Value

Returns a list with the followin values:

parameters Final value of parameters at over which the optimization takes place.
objective Final value of the objective function.
message Statement of the reason for termination.
grad.norm Final norm of the objective gradient.
iterations Total number of iterations before terminiation.
f.evals Total number of residual evaluations before the termination.
g.evals Total number of jacobian evaluations before the termination.
hessian Final value of the Hessian matrix, only if hessian is supplied intially.
scale Final value of scale vector.

See Also

nlminb, predict.tps, predict.krig, predict.nnreg

Examples

tps(BD[,1:4],BD$lnya,scale.type="range") -> fit # fitting a DNA strand
# displacement amplification surface to various buffer compositions
surface(fit) # plots fitted surface and contours
optim(fit) # find surface optimum


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