BootDark

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Description

A script using bootstrap techniques to calculate confidence intervals for parameter estimates from a 'dark' object.

Usage

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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.

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.

Value

Returns a list 'out'

out$time

times of observations

out$thrs

thresholds

out$opt

optimised parameter estimates

out$Mod

the name of the optimal model

out$Pn

number of parameters needed to describe the data

out$AIC

the AICc scores for the three models

out$fit

fitted values for the optimal parameter estimates

out$resd

residuals of the best fits

out$R2

the coefficient of determination

out$Bootstrap

bootstrap parameter estimates, 2.5%, 50% and 97.5%

out$weight

the reciprocal of the CI

out$valid

nn indication whether the parameter estimate is valid

out$data

the source of the data

out$call

updates the call label on the object

Author(s)

Jeremiah MF Kelly

Faculty of Life Sciences, The University of Manchester, M13 9PL, UK

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.

Examples

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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)
BootDark(tmp3,50)