| cequre | R Documentation |
Implementation of censored quantile regression of Huang (2010), with incorporation of an upper bound related to the identification limit on probability scale as described in Huang (2013).
cequre(x,dlt,z,epsi=0.05,taus=numeric(0),res=0,
resam.dist=FALSE,nbps=3*length(x))
x |
follow-up time. |
dlt |
censoring indicator: 1 - event, 0 - censored. |
z |
matrix of covariates (intercept not included): each column corresponds to a covariate. |
epsi |
parameter for the upper bound related to the identification limit on probability scale. |
taus |
(increasing) tau values at which quantile coefficient is of interest. |
res |
number of resampling iterations for variance estimation: res=200 is typically sufficient for variance estimation, but res needs to be much larger for confidence band construction. |
resam.dist |
resampling distribution to be reported or not. |
nbps |
maximum storage size for quantile coefficient: 3*length(x is typically sufficient. |
curve |
estimated (piecewise-constant) quantile coefficient: each column corresponds to a jump point (the intercept is followed by slope coefficients, and final element is tau, the probability index.) |
tau.bnd |
upper bound of tau such that determinant of the at-risk matrix (for uncensored observations) is at least epsi^# regression coefficients times the initial value, subject to provided storage limit (nbps). |
bt |
estimated quantile coefficient at taus, only available if taus is specified. |
va |
variance estimate associated with bt, only available if taus is specified and res>0. As is resampling based, the variance estimate can be slightly different over multiple runs unless seed for the random number generator is reset each time. |
dist |
resampling distribution with res resampled curves: dist[ , ,1] through dist[ , ,res], only available if res>0 and resam.dist=TRUE. |
dist.lgth |
lengths of resampled curves, only available if res>0 and resam.dist=TRUE. |
Huang, Y. (2010) Quantile calculus and censored regression, The Annals of Statistics 38, 1607–1637.
Huang, Y. (2013) Fast censored linear regression. Scandinavian Journal of Statistics 40, 789–806.
## simulate a dataset following Scenario 1 of Table 1 in Huang (2010)
num <- 200
beta <- c(.5, .5)
cvt.1 <- as.numeric(runif(num)<0.5)
cvt.2 <- runif(num)
resid <- rexp(num)
tres <- 1-exp(-resid)
event.t <- log(resid)+beta[1]*cvt.1*ifelse(tres<.4,tres/.4,1)+beta[2]*cvt.2
censr.t <- log(runif(num, 0, 5))
x <- pmin(event.t, censr.t)
dlt <- as.numeric(event.t<=censr.t)
## run censored quantile regression
fit <- cequre(x,dlt,cbind(cvt.1,cvt.2),taus=.1*seq(1,7,2),res=200)
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.