A script using bootstrap techniques to calculate confidence intervals for parameter estimates from a 'dark' object.
Usage
BootDark(obj, R, graph, progress = F)
Arguments
obj
A 'dark' object.
R
The number of repeats for the bootstrap calculations.
graph
A flag to indicate whether a figure should be drawn.
progress
A flag to indicate whether a progress bar should be drawn to the console. This might be preferred if using a large number of repeats.
Value
Returns a list 'out'
out$timetimes of observations
out$thrsthresholds
out$optoptimised parameter estimates
out$Modthe name of the optimal model
out$Pnnumber of parameters needed to describe the data
out$AICthe AICc scores for the three models
out$fitfitted values for the optimal parameter estimates
out$resdresiduals of the best fits
out$R2the coefficient of determination
out$Bootstrapbootstrap parameter estimates, 2.5%, 50% and 97.5%
out$weightthe reciprocal of the CI
out$validnn indication whether the parameter estimate is valid
out$datathe source of the data
out$callupdates the call label on the object
Details
The script calculates bootstrap estimates of confidence intervals by sampling the residuals without replacement. The seven parameter model 'P7c' is always used. If 'P3' or 'P5c' have been found elsewhere to be a better fit then this will be confirmed by bootstrapping the 'P7c' model.
References
B. Efron. Bootstrap methods: another look at the jackknife. The Annals of Statistics, 7(1):1-26, 1979.
B. Efron. Nonparametric estimates of standard error: The jackknife, the bootstrap and other methods. Biometrika, 68(3):589, 1981.