coxphw.control {coxphw}  R Documentation 
This is used to set various numeric parameters controlling a Cox model fit using coxphw
.
Typically it would only be used in a call to coxphw
.
coxphw.control(iter.max = 200, maxhs = 5, xconv = 1e4, gconv = 1e4, maxstep = 1, round.times.to = 0.00001, add.constant = 0, pc = TRUE, pc.time = TRUE, normalize = TRUE)
iter.max 
maximum number of iterations to attempt for convergence. Default is 200. 
maxhs 
maximum number of stephalvings per iterations. Default is 5. The increments of the
parameter vector in one NewtonRhaphson iteration step are halved, unless the new
pseudolikelihood is greater than the old one, maximally doing 
xconv 
specifies the maximum allowed change in standardized parameter estimates to declare convergence. Default is 0.0001. 
gconv 
specifies the maximum allowed change in score function to declare convergence. Default is 0.0001. 
maxstep 
specifies the maximum change of (standardized) parameter values allowed in one iteration. Default is 1. 
round.times.to 
rounds survival times to the nearest number that is a multiple of

add.constant 
this number will be added to all times. It can be used if some survival times are exactly 0. Default is 0. 
pc 
if set to TRUE, it will orthogonalize the model matrix to speed up convergence. Default is TRUE. 
pc.time 
if set to TRUE, it will orthogonalize timedependent covariates (i.e., interactions of covariates with functions of time) to speed up convergence. Default is TRUE. 
normalize 
if set to TRUE, weights are normalized such that their sum is equal to the number of events. This may speed up or enable convergence, but has no consequences on the estimated regression coefficients. 
A list containing the values of each of the above constants
Daniela Dunkler