boot_gaussian {EquiSurv} | R Documentation |
Parametric Bootstrap of time-to-event data following a gaussian distribution
Description
Function generating bootstrap data according to a gaussian distribution (specified by a model parameter \theta
),
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.
Usage
boot_gaussian(t0, B = 1000, theta, C, N)
Arguments
t0 |
time point of interest |
B |
number of bootstrap repetitions. The default is B=1000 |
theta |
parameter of the gaussian distribution, theta=(mean,sd) |
C |
rate of the exponential distribution specifiying the censoring |
N |
size of the dataset = number of observations |
Value
A vector of length B containing the estimated survival at t0
Examples
t0<-2
N<-30
C<-1
boot_gaussian(t0=t0,theta=c(1.7,1),C=C,N=N)
[Package EquiSurv version 0.1.0 Index]