IPCWdf {survivalREC} | R Documentation |
Provides estimates for the bivariate distribution function based on the Inverse Probability of Censoring Weighting estimator (IPCW).
IPCWdf(object, x, y, covariate, cov.value, bw, window = "gaussian")
object |
An object of class multidf. |
x |
The first time for obtaining estimates for the bivariate distribution function. |
y |
The second time for obtaining estimates for the bivariate distribution function. |
covariate |
Name of the quantitative covariate. |
cov.value |
The value of the quantitative covariate. |
bw |
A single numeric value to compute a kernel density bandwidth. Use
|
window |
A character string specifying the desired kernel. See details
below for possible options. Defaults to |
Vector with the IPWC estimates for the bivariate distribution function.
Gustavo Soutinho and Luis Meira-Machado.
Gustavo Soutinho and Luis Meira-Machado
de Una-Alvarez, J. and Meira-Machado, L. (2008). A simple estimator of the bivariate distribution function for censored gap times, Statistics and Probability Letters 78, 2440-2445.
KMWdf
, LDMdf
, LINdf
and
WCHdf
.
data("bladder4state")
b3state<-multidf(gap1=bladder4state$y1, event1=bladder4state$d1,
gap2=bladder4state$y2, status=bladder4state$d2,
size=bladder4state$size)
b3size<-multidf(gap1=bladder3$t1, event1=bladder3$d1,
gap2=bladder3$t2-bladder3$t1,status=bladder4state$d2,
size=bladder3$size)
library(KernSmooth)
IPCWdf(object=b3state, x=13, y=15, covariate="size", cov.value=3,
window = "gaussian")
IPCWdf(object=b3state, x=13, y=15, covariate="size", bw=2, cov.value=3,
window = "gaussian")
IPCWdf(object=b3size, x=13, y=15, covariate="size", cov.value=3,
window = "gaussian")
IPCWdf(object=b3size, x=13, y=15, covariate="size", bw=2, cov.value=3,
window = "gaussian")