Description Usage Arguments Details Value References See Also Examples
Implementation of the kernel discrete hazard rate estimator of Tutz and Pritscher (1996) based on the discrete Habbema
kernel. The estimate is used for comparison with the semiparametric estimate deveoped in Tutz and Pritscher (1996).
1 | TutzPritscher(xin, cens, xout)
|
xin |
A vector of data points. Missing values not allowed. |
cens |
Censoring indicators as a vector of 1s and zeros, 1's indicate uncensored observations, 0's correspond to censored obs. |
xout |
The grid points where the estimates will be calculated. |
The discrete kernel estimate of Tutz and Pritscher (1996) is defined by
λ(t_m|v) =
where w_m is the discrete Habbema kernel.
Returns a vector with the values of the hazard rate estimates at x=xout.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 | options(echo=FALSE)
xin<-c(7,34,42,63,64, 74, 83, 84, 91, 108, 112,129, 133,133,139,140,140,146,
149,154,157,160,160,165,173,176,185, 218,225,241, 248,273,277,279,297,
319,405,417,420,440, 523,523,583, 594, 1101, 1116, 1146, 1226, 1349,
1412, 1417)
cens<-c(1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,
0,1,0,1,1,1,1,1,0,1,1,1,0,1)
xin<-xin/30.438 #Adjust the data
storage.mode(xin)<-"integer" # turn the data to integers
xout<-seq(1,47, by=1) # define the grid points to evaluate the estimate
arg<-TutzPritscher(xin,cens,xout) #Discrete kernel estimate
plot(xout, arg, type="l", ylim=c(0, .35), lty=2, col=6) # plot the estimate
argSM<-lambdahat(xin, cens, xout) #crude nonparametric estimate
lines(xout, argSM, lty=3, col=5) # plot the crude estimate
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