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)
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
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.
Author
Jeremiah MF Kelly
Mumac Ltd, SK7 6NR, GB
Details
To reduce the possibility of selecting non-optimal parameter estimates, the optimisation is repeated in the region of initial estimates. The
References
Nelder, J.A.; Mead, R. 1965: A simplex for function minimization. Comput. J. 7, 308-313