Description Usage Arguments Value Examples
View source: R/boot_logistic.R
Function generating bootstrap data according to a logistic distribution (specified by a model parameter θ), assuming exponentially distributed right-censoring (specified by a rate C). After data generation again a model is fitted and evaluated at a pre-specified time point t_0 yielding the response vector.
1 | boot_logistic(t0, B = 1000, theta, C, N)
|
t0 |
time point of interest |
B |
number of bootstrap repetitions. The default is B=1000 |
theta |
parameter of the logistic distribution, theta=(location,scale) |
C |
rate of the exponential distribution specifiying the censoring |
N |
size of the dataset = number of observations |
A vector of length B containing the estimated survival at t0
1 2 3 4 | t0<-2
N<-30
C<-1
boot_logistic(t0=t0,theta=c(1,0.4),C=C,N=N)
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