| myLLfun {ELYP} | R Documentation |
Compute Baseline Hazard for the Given Data and Parameters beta1, beta2, lam. Also Compute the empirical likelihood value.
Description
This function is similar to fitYP3. Just streamline input and output.
Usage
myLLfun(mle, dataMat, fun)
Arguments
mle |
a vector of length 3, containing the parameter values: beta1, beta2 and lam. They do not have to be the MLE. |
dataMat |
a matrix of 4 by n. But the 4th row do not matter, since alpha=0 here always. |
fun |
a function, used in the definition of int f(t)dH(t)= Mulam. |
Details
We assume a Y-P model. and with the given parameters (in the input mle) we compute the baseline hazard and compute the (parameter constrained) empirical likelihood value.
Value
A list with the following components:
Mulam |
The value of int f(t) d H(t) for corresponding lam. Notice lam, beta1, beta2 determine the baseline H(t). |
Loglik |
The log empirical likelihood. |
Author(s)
Mai Zhou
References
Zhou, M. (2002). Computing censored empirical likelihood ratio by EM algorithm. Tech Report, Univ. of Kentucky, Dept of Statistics
Examples
## censored regression with one right censored observation.
## we check the estimation equation, with the MLE inside myfun7.
y <- c(3, 5.3, 6.4, 9.1, 14.1, 15.4, 18.1, 15.3, 14, 5.8, 7.3, 14.4)
x <- c(1, 1.5, 2, 3, 4, 5, 6, 5, 4, 1, 2, 4.5)
d <- c(1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0)