| BJfindL2 {ELYP} | R Documentation |
Find the Wilks Confidence Interval Lower Bound for Betafun from the 2 dimensional Buckley-James Empirical Likelihood Ratio Function
Description
This function uses simple search to find the lower level (default 95%) 1 parameter Wilks confidence limits based on the Buckley-James empirical likelihood test function for two dimensional beta's. Betafun determines the 1 parameter we are finding the lower bound.
Usage
BJfindL2(NPmle, ConfInt, LLRfn, Betafun, dataMat, level=3.84)
Arguments
NPmle |
a 2-d vector: the NPMLEs: beta1 hat and beta2 hat. |
ConfInt |
a vector of length 2. Approx. length of the 2 conf. intervals for beta1 and beta2. |
LLRfn |
a function that returns -2LLR value. |
Betafun |
a function that takes the input of 2 parameter values (beta1,beta2) and returns a parameter that we wish to find the confidence Interval lower Value. |
dataMat |
matrix of covariates |
level |
confidence level. Use chi-square(df=1), but calibration possible. |
Details
Basically we repeatedly testing the value of the 2 parameters, finding the -2LLR values, until we find those Betafun which the -2 log likelihood Ratio value is equal to 3.84 (or other level, if set differently).
Value
A list with the following components:
Lower |
the lower confidence bound. |
minParameterNloglik |
Final values of the 2 parameters, and the log likelihood. |
Author(s)
Mai Zhou
References
Zhou, M. and Li, G. (2006). Computing censored empirical likelihood ratio by EM algorithm. JCGS
Examples
## See the Rd file of BJfindU2 for example.