MultiStart: MultiStart

In emkayoh/Dark: The Analysis of Dark Adaptation Data

MultiStart

Description

Given a dark object, obj, this function repeatedly optimises the parameters in the vicinity of the seed array. The width of the search is dependent upon the value of spread.

Usage

MultiStart(obj, repeats, draw, spread, debug)

Arguments

obj	A dark object containing at least; obj$time time obj$thrs thresholds obj$init an initial estimate of the parameters of dark adaptation.
repeats	The number of times the algorithm is repeated
draw	A flag indicating whether a figure should be drawn.
spread	The amount by which the seed array should be varied. A larger value gives a greater range of possible starting points.
debug	A flag used in debugging the software.

Details

To reduce the possibility of selecting non-optimal parameter estimates, the optimisation is repeated in the region of initial estimates. The

Value

Returns a list;

time	times of threshold setting
out$thrs	observed thresholds
out$resid	residuals
out$fit	optimal fitted values
out$thet	seed parameters if test data
out$sse	sum of squared residuals if test data
out$data	source of the data
out$opt	optimal parameter estimates of the chosen model
out$Mod	name of the optimal model
out$Pn	the number of parameters needed to describe the data
out$AIC	array of AICc scores
out$val	calculated sum of squared residuals
out$R2	the coefficient of determination
out$warning	if none of the nearby values converge
out$call	updates the function call label

Author(s)

Jeremiah MF Kelly

Mumac Ltd, SK7 6NR, GB

References

Nelder, J.A.; Mead, R. 1965: A simplex for function minimization. Comput. J. 7, 308-313

Examples

set.seed(1234)
Time<- seq(0,20)
tmp<- TestData(Time)
P<-Start(tmp,1000)
MSC<-ModelSelect(tmp, P)
tmp2<-BestFit(tmp, MSC)
tmp3<-MultiStart(tmp2,10)

emkayoh/Dark documentation built on Jan. 22, 2025, 3:17 a.m.