Qcoxph.control | R Documentation |
Auxiliary function for controlling Qcoxph
fitting. Estimation proceeds in three steps: (i) evaluation of starting points; (iia) stochastic gradient-based optimization (iib) standard gradient-based optimization; and (iii) Newton-Raphson. Step (i) is based on a preliminary fit of a Cox model via coxph
. Steps (iia) and (iib) find an approximate solution, and make sure that the Jacobian matrix is well-defined. Finally, step (iii) finds a more precise solution.
Qcoxph.control(tol = 1e-8, maxit, safeit, alpha0, display = FALSE)
tol |
tolerance for convergence of Newton-Raphson algorithm, default is 1e-8. |
maxit |
maximum number of iterations of Newton-Raphson algorithm. If not provided, a default is computed as |
safeit |
maximum number of iterations of gradient-search algorithm. If not provided, a default is computed as |
alpha0 |
step size for the preliminary gradient-based iterations. If estimation fails, you can try choosing a small value of |
display |
Logical. If |
If called with no arguments, Qcoxph.control()
returns a list with the current settings of these parameters. Any arguments included in the call sets those parameters to the new values, and then silently returns.
A list with named elements as in the argument list
Gianluca Sottile <gianluca.sottile@unipa.it> Paolo Frumento <paolo.frumento@unipi.it>
Qcoxph
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