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.

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.


[Package ELYP version 0.7-5 Index]