Description Usage Arguments Value Author(s) Examples
Evaluates the linear predictor from a Cox proportional Hazards model fitted by sprinter
.
1 2 |
object |
Cox proportional Hazards model from a |
newdata |
|
... |
additional arguments. |
The linear predictor, a vector of length n.new
, is returned.
Isabell Hoffmann isabell.hoffmann@uni-mainz.de
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 | simulation <- simul.int(287578,n = 200, p = 500,
beta.int = 1.0,
beta.main = 0.9,
censparam = 1/20,
lambda = 1/20)
data <- simulation$data
simulation$info
set.seed(123)
## Not run:
testcb <- sprinter( x=data[,1:500],
time = data$obs.time,
status= data$obs.status,
repetitions = 10,
mandatory = c("ID1","ID2"),
n.inter.candidates = 1000,
screen.main = fit.CoxBoost,
fit.final = fit.CoxBoost,
args.screen.main = list(seed=123,stepno = 10, K = 10,
criterion ='pscore', nu = 0.05),
parallel = FALSE, trace=TRUE)
summary(testcb)
# true coefficients:
# Clin.cov1 Clin.cov2 ID5:ID6 ID7:ID8
# 0.9 -0.9 1 -1
# Simulate New Data:
newSimulation <- simul.int(12345,n = 200, p = 500,
beta.int = 1.0,
beta.main = 0.9,
censparam = 1/20,
lambda = 1/20)
newdata <- newSimulation$data
newSimulation$info
predict(testcb, newdata = newdata[,1:500])
## End(Not run)
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