boot.nonparTrans {depCensoring} | R Documentation |
Nonparametric bootstrap approach for a Semiparametric transformation model under dependent censpring
Description
This function estimates the bootstrap standard errors for the finite-dimensional model parameters and for the non-parametric transformation function. Parallel computing using foreach has been used to speed up the estimation of standard errors.
Usage
boot.nonparTrans(init, resData, X, W, n.boot, n.iter, eps)
Arguments
init |
Initial values for the finite dimensional parameters obtained from the fit of |
resData |
Data matrix with three columns; Z = the observed survival time, d1 = the censoring indicator of T and d2 = the censoring indicator of C. |
X |
Data matrix with covariates related to T |
W |
Data matrix with covariates related to C. |
n.boot |
Number of bootstraps to use in the estimation of bootstrap standard errors. |
n.iter |
Number of iterations; the default is |
eps |
Convergence error. This is set by the user in such away that the desired convergence is met; the default is |
Value
Bootstrap standard errors for parameter estimates and for estimated cumulative hazard function.