| BootDark {Dark} | R Documentation |
BootDark
Description
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. |
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
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)