crq.fit {crq} | R Documentation |
Function controlling the fitting of censored quantile regression models
crq.fit(x, y, cen, weights, method, mw = 20 , ginit = 0.001, gstep = NULL)
x |
the design matrix |
y |
the response vector typically in log(event time) (AFT) form |
cen |
censoring indicator: usually 0 for censored, 1 for uncensored. No provision for interval censoring (yet). |
weights |
weights to be used for fitting see crq . |
method |
method to be used: either "grid" or "pivot". |
mw |
Maximal number of allowed calls to weighted rq (to handle possible degeneracy). Only relevant for method = "pivot". |
gstep |
spacing of points of evaluation only relevant for method = "grid",
defaults to min(0.01,1/(2*length(y)^{.7})) . |
ginit |
initial point of evaluation only relevant for method = "grid", defaults to 0.001. |
See {crq
}
sol |
A matrix with (p+2) rows: the first row is the taus (in (0,1)) corresponding to the fitted model parameters. The next p rows are the fitted parameters betahat (tau), and the final row contains entries predicting the conditional quantiles of the response at the mean of the design: xbar ' betahat (tau). |
Isplit |
Indices of split censored observations. |
tausplit |
Corresponding tau values. |
status |
Status of censored observations: 0: not censored 1: split (crossed) censored 2: deleted censored as below tau = 0 solution 3: above last (maximal tau) solution |
Stephen Portnoy & Tereza Neocleous